scholarly journals Statistical Forecasting : Third Wave of COVID-19-With an Application to India

2021 ◽  
Author(s):  
Sabara Parshad Rajeshbhai ◽  
Subhra Sankar Dhar ◽  
Shalabh Shalabh
Keyword(s):  
Gaussian Mixture Model ◽  
Gaussian Mixture ◽  
Third Wave ◽  
Statistical Methodology ◽  
Gaussian Distributions ◽  
Wave Modelling ◽  
The Third ◽  
Entire World ◽  
The Impact ◽  
Mixture Of Gaussian

The pandemic due to the SARS-CoV-2 virus impacted the entire world in different waves. An important question that arise after witnessing the first and second waves of COVID-19 is - Will the third wave also arrive and if yes, then when. Various types of methodologies are being used to explore the arrival of third wave. A statistical methodology based on the fitting of mixture of Gaussian distributions is explored in this paper and the aim is to forecast the third wave using the data on the first two waves of pandemic. Utilizing the data of different countries that are already facing the third wave, modelling of their daily cases data and predicting the impact and timeline for the third wave in India is attempted in this paper. The Gaussian mixture model based on algorithm for clustering is used to estimate the parameters.

scholarly journals Detection of Unknown DDoS Attacks with Deep Learning and Gaussian Mixture Model

2021 ◽  
Vol 11 (11) ◽  
pp. 5213
Author(s):  
Chin-Shiuh Shieh ◽  
Wan-Wei Lin ◽  
Thanh-Tuan Nguyen ◽  
Chi-Hong Chen ◽  
Mong-Fong Horng ◽  
...  
Keyword(s):  
Deep Learning ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Denial Of Service ◽  
Gaussian Mixture ◽  
Mitigation Measures ◽  
Distribution Model ◽  
Ddos Attacks ◽  
Open Set ◽  
The Impact

DDoS (Distributed Denial of Service) attacks have become a pressing threat to the security and integrity of computer networks and information systems, which are indispensable infrastructures of modern times. The detection of DDoS attacks is a challenging issue before any mitigation measures can be taken. ML/DL (Machine Learning/Deep Learning) has been applied to the detection of DDoS attacks with satisfactory achievement. However, full-scale success is still beyond reach due to an inherent problem with ML/DL-based systems—the so-called Open Set Recognition (OSR) problem. This is a problem where an ML/DL-based system fails to deal with new instances not drawn from the distribution model of the training data. This problem is particularly profound in detecting DDoS attacks since DDoS attacks’ technology keeps evolving and has changing traffic characteristics. This study investigates the impact of the OSR problem on the detection of DDoS attacks. In response to this problem, we propose a new DDoS detection framework featuring Bi-Directional Long Short-Term Memory (BI-LSTM), a Gaussian Mixture Model (GMM), and incremental learning. Unknown traffic captured by the GMM are subject to discrimination and labeling by traffic engineers, and then fed back to the framework as additional training samples. Using the data sets CIC-IDS2017 and CIC-DDoS2019 for training, testing, and evaluation, experiment results show that the proposed BI-LSTM-GMM can achieve recall, precision, and accuracy up to 94%. Experiments reveal that the proposed framework can be a promising solution to the detection of unknown DDoS attacks.

scholarly journals Multigrid Nonlocal Gaussian Mixture Model for Segmentation of Brain Tissues in Magnetic Resonance Images

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Yunjie Chen ◽  
Tianming Zhan ◽  
Ji Zhang ◽  
Hongyuan Wang
Keyword(s):  
Magnetic Resonance ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Magnetic Resonance Images ◽  
Intensity Inhomogeneity ◽  
Mr Images ◽  
Proposed Model ◽  
Brain Mr Images ◽  
The Impact

We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM) is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM) is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.

Render unto Caesar Just a Little Bit Longer: The Relationship between Constitutional Reforms and Executive Survival

2021 ◽  
pp. 1-22
Author(s):  
Tofigh Maboudi ◽  
Ghazal P. Nadi ◽  
Todd A. Eisenstadt
Keyword(s):  
Term Limits ◽  
Institutional Constraints ◽  
Third Wave ◽  
Political Leaders ◽  
Constitutional Order ◽  
The Third ◽  
Constitutional Reforms ◽  
The Impact ◽  
First Time ◽  
The Relationship

Abstract Since the third wave of democracy, term limits have become a popular fixture of most constitutions intended to constrain the executive. Yet, recent constitutional reforms around the world show that presidents seeking re-election sometimes overturn the entire constitutional order to extend their power. What is the impact of these constitutional manipulations on the longevity of the executive in office? Using survival analysis of all political leaders and national constitutions from 1875 to 2015, this article demonstrates, for the first time, that when ‘authoritarian-aspiring’ presidents remove constitutional term limits, they increase their stay in office by more than 40%. Our findings contrast with a widely held position in the comparative authoritarian literature suggesting that dictators survive longer under institutional constraints. On the contrary, we argue that by removing constitutional barriers, rulers consolidate more power at the expense of their most ambitious allies and can stay in power longer.

scholarly journals Assessing the impact of widespread respirator use in curtailing COVID-19 transmission in the USA

2021 ◽  
Vol 8 (9) ◽  
pp. 210699
Author(s):  
Calistus N. Ngonghala ◽  
James R. Knitter ◽  
Lucas Marinacci ◽  
Matthew H. Bonds ◽  
Abba B. Gumel
Keyword(s):  
Dynamic Models ◽  
Effective Control ◽  
Natural Immunity ◽  
Third Wave ◽  
Respiratory Protection ◽  
The Third ◽  
Surgical Masks ◽  
The Usa ◽  
Baseline Levels ◽  
The Impact

Dynamic models are used to assess the impact of three types of face masks (cloth masks, surgical/procedure masks and respirators) in controlling the COVID-19 pandemic in the USA. We showed that the pandemic would have failed to establish in the USA if a nationwide mask mandate, based on using respirators with moderately high compliance, had been implemented during the first two months of the pandemic. The other mask types would fail to prevent the pandemic from becoming established. When mask usage compliance is low to moderate, respirators are far more effective in reducing disease burden. Using data from the third wave, we showed that the epidemic could be eliminated in the USA if at least 40% of the population consistently wore respirators in public. Surgical masks can also lead to elimination, but requires compliance of at least 55%. Daily COVID-19 mortality could be eliminated in the USA by June or July 2021 if 95% of the population opted for either respirators or surgical masks from the beginning of the third wave. We showed that the prospect of effective control or elimination of the pandemic using mask-based strategy is greatly enhanced if combined with other non-pharmaceutical interventions (NPIs) that significantly reduce the baseline community transmission. By slightly modifying the model to include the effect of a vaccine against COVID-19 and waning vaccine-derived and natural immunity, this study shows that the waning of such immunity could trigger multiple new waves of the pandemic in the USA. The number, severity and duration of the projected waves depend on the quality of mask type used and the level of increase in the baseline levels of other NPIs used in the community during the onset of the third wave of the pandemic in the USA. Specifically, no severe fourth or subsequent wave of the pandemic will be recorded in the USA if surgical masks or respirators are used, particularly if the mask use strategy is combined with an increase in the baseline levels of other NPIs. This study further emphasizes the role of human behaviour towards masking on COVID-19 burden, and highlights the urgent need to maintain a healthy stockpile of highly effective respiratory protection, particularly respirators, to be made available to the general public in times of future outbreaks or pandemics of respiratory diseases that inflict severe public health and socio-economic burden on the population.

scholarly journals Impact of COVID-19 Variants on the Second Wave in India and Subsequent Discretion of Possibilities of the Third Wave

2021 ◽  
pp. 115-126
Author(s):  
Sudarshan Ramaswamy ◽  
Meera Dhuria ◽  
Sumedha M. Joshi ◽  
Deepa H Velankar
Keyword(s):  
Herd Immunity ◽  
Sir Model ◽  
The Other ◽  
Third Wave ◽  
Focal Points ◽  
Current Analysis ◽  
The Third ◽  
The Impact ◽  
Second Wave ◽  
Insight Into

Introduction: Epidemiological comprehension of the COVID-19 situation in India can be of great help in early prediction of any such indications in other countries and possibilities of the third wave in India as well. It is essential to understand the impact of variant strains in the perspective of the rise in daily cases during the second wave – Whether the rise in cases witnessed is due to the reinfections or the surge is dominated by emergence of mutants/variants and reasons for the same. Overall objective of this study is to predict early epidemiological indicators which can potentially lead to COVID-19 third wave in India. Methodology: We analyzed both the first and second waves of COVID-19 in India and using the data of India’s SARS-CoV-2 genomic sequencing, we segregated the impact of the Older Variant (OV) and the other major variants (VOI / VOC).  Applying Kermack–McKendrick SIR model to the segregated data progression of the epidemic in India was plotted in the form of proportion of people infected. An equation to explain herd immunity thresholds was generated and further analyzed to predict the possibilities of the third wave. Results: Considerable difference in ate of progression of the first and second wave was seen. The study also ascertains that the rate of infection spread is higher in Delta variant and is expected to have a higher threshold (>2 times) for herd immunity as compared to the OV. Conclusion: Likelihood of the occurrence of the third wave seems unlikely based on the current analysis of the situation, however the possibilities cannot be ruled out. Understanding the epidemiological details of the first and second wave helped in understanding the focal points responsible for the surge in cases during the second wave and has given further insight into the future.

scholarly journals The Foucault Effect in Organization Studies

2017 ◽  
Vol 40 (2) ◽  
pp. 155-182 ◽  
Author(s):  
Sverre Raffnsøe ◽  
Andrea Mennicken ◽  
Peter Miller
Keyword(s):  
Twentieth Century ◽  
The Self ◽  
Third Wave ◽  
Organization Studies ◽  
Linguistic Turn ◽  
The Third ◽  
The Past ◽  
Organizational Scholarship ◽  
The Impact ◽  
Second Wave

Since the establishment of Organization Studies in 1980, Michel Foucault’s oeuvre has had a remarkable and continuing influence on its field. This article traces the different ways in which organizational scholars have engaged with Foucault’s writings over the past thirty years or so. We identify four overlapping waves of influence. Drawing on Foucault’s Discipline and Punish, the first wave focused on the impact of discipline, and techniques of surveillance and subjugation, on organizational practices and power relations. Part of a much wider ‘linguistic’ turn in the second half of the twentieth century, the second wave led to a focus on discourses as intermediaries that condition ways of viewing and acting. This wave drew mainly on Foucault’s early writings on language and discourse. The third wave was inspired by Foucault’s seminal lectures on governmentality towards the end of the 1970s. Here, an important body of international research investigating governmental technologies operating on subjects as free persons in sites such as education, accounting, medicine and psychiatry emerged. The fourth and last wave arose out of a critical engagement with earlier Foucauldian organizational scholarship and sought to develop a more positive conception of subjectivity. This wave draws in particular on Foucault’s work on asceticism and techniques of the self towards the end of his life. Drawing on Deleuze and Butler, the article conceives the Foucault effect in organization studies as an immanent cause and a performative effect. We argue for the need to move beyond the tired dichotomies between discipline and autonomy, compliance and resistance, power and freedom that, at least to some extent, still hamper organization studies. We seek to overcome such dichotomies by further pursuing newly emerging lines of Foucauldian research that investigate processes of organizing, calculating and economizing characterized by a differential structuring of freedom, performative and indirect agency.

scholarly journals One wave or another in the pandemic: Psychological well-being during the third COVID-19 wave

2021 ◽  
Author(s):  
Michela Marchetti ◽  
Daniele Gatti ◽  
Lucio Inguscio ◽  
Giuliana Mazzoni
Keyword(s):  
Positive Emotions ◽  
Well Being ◽  
Mental States ◽  
Protective Role ◽  
Perceived Usefulness ◽  
Third Wave ◽  
The Third ◽  
Data Driven Approach ◽  
Restrictive Measures ◽  
The Impact

After a year from the emergence of the Coronavirus disease (COVID-19) on February 2020, between March and May 2021 Italy faced its third wave of infections. Previous studies have shown that in the first phases of the pandemic certain factors had a protective role against distress. However, as the months in the pandemic went by, people’s feelings and experiences significantly changed and little is known regarding the role of possible protective variables after prolonged pandemic situations. In the present study we aimed to investigate the impact of several behavioral variables on individuals’ mental states and emotions experienced during the third COVID-19 wave in Italy. 454 Italian adults were asked questions regarding the intensity of mental states and emotions experienced, the perceived usefulness of lockdown, the feeling of living a normal life, and the coping strategies implemented to face the pandemic. Using a data driven approach, we calculated the best model on the participation of each factor in explaining participants’ emotions and mental states. Our findings indicate that the presence of acceptance attitudes toward restrictive measures and the implementation of recreational activities helped participants face a prolonged pandemic with positive emotions.

scholarly journals Assessing the impact of widespread respirator use in curtailing COVID-19 transmission in the United States

2021 ◽  
Author(s):  
Calistus N Ngonghala ◽  
James R Knitter ◽  
Lucas Marinacci ◽  
Matthew H Bonds ◽  
Abba B Gumel
Keyword(s):  
United States ◽  
Dynamic Models ◽  
The United States ◽  
Effective Control ◽  
Third Wave ◽  
Respiratory Protection ◽  
The Third ◽  
Surgical Masks ◽  
The Us ◽  
The Impact

Dynamic models are used to assess the impact of three types of face masks − cloth masks, surgical/procedure masks and respirators − in controlling the COVID-19 pandemic in the United States. We showed that the pandemic would have failed to establish in the US if a nationwide mask mandate, based on using respirators with moderately-high compliance, had been implemented during the first two months of the pandemic. The other mask types would fail to prevent the pandemic from becoming established. When mask usage compliance is low to moderate, respirators are far more effective in reducing disease burden. Using data from the third wave, we showed that the epidemic could be eliminated in the US if at least 40% of the population consistently wore respirators in public. Surgical masks can also lead to elimination, but requires compliance of at least 55%. Daily COVID-19 mortality could be eliminated in the US by June or July 2021 if 95% of the population opted for either respirators or surgical masks from the beginning of the third wave. We showed that the prospect of effective control or elimination of the pandemic using mask-based strategy is greatly enhanced if combined with other nonpharmaceutical interventions that significantly reduce the baseline community transmission. This study further emphasizes the role of human behavior towards masking on COVID-19 burden, and highlights the urgent need to maintain a healthy stockpile of highly-effective respiratory protection, particularly respirators, to be made available to the general public in times of future outbreaks or pandemics of respiratory diseases that inflict severe public health and socio-economic burden on the population.

scholarly journals The Impact of the Third Wave of COVID 19 in Patients with Chronic Hepatitis C

2020 ◽  
Vol 1 (1) ◽  
pp. 014-014
Author(s):  
Daniela Mariano Carvalho-Louro
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis C ◽  
Liver Diseases ◽  
Daily Life ◽  
Third Wave ◽  
Severe Liver ◽  
Treatment Progress ◽  
The Third ◽  
Advanced Stages ◽  
The Impact

Letter to EditorIn the practical clinical of Hepatology, the focus of daily life has been the treatment of patients with severe liver diseases, such as cirrhosis and liver cancer. Of all the liver diseases responsible for cirrhosis development, hepatitis C had made the most treatment progress. In a few years, it evolved from drugs with low efficacy and many side effects to highly safe medications with high cure rates.For hepatologists who manage critically ill patients with advanced stages of liver diseases, finding an effective Hepatitis C drug was a great encouragement, a huge motivation to continue believing in clinical research.

A Method to Calculate Carbon Footprint of Processing Sectors Based on Gaussian Mixture Model

2013 ◽  
Vol 415 ◽  
pp. 692-696 ◽  
Author(s):  
Xue Ping Liu ◽  
Zhi Shan Liu ◽  
Dong Xiang ◽  
Lang Gao ◽  
Yang Cui ◽  
...  
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Carbon Footprint ◽  
Gaussian Mixture ◽  
Statistical Character ◽  
The Impact

Carbon footprint is used to measure the impact of products or services on environment in recently years. The main technology in evaluating carbon footprint comes from LCA and PAS2050. However, the detail in calculating carbon footprint is not well studied. In this paper, the focus was drawn on the processing sectors. Due to the statistical character of data collected in processing sectors, the GMM (Gaussian Mixture Model) is introduced to calculate carbon footprint. With this method, the statistical meaning of carbon footprint data is well understood.

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