scholarly journals APPLICATION OF THE LOGISTIC FUNCTION TO ASSESS THE IMPACT OF THE ENVIRONMENT ON SEA FERRY, CRUISE LINES AND MARINE PASSENGER TERMINALS

2020 ◽  
Vol 12 (4) ◽  
pp. 627-639
Author(s):  
Nikolai N. Maiorov ◽  
◽  
Vladimir A. Fetisov ◽  
Keyword(s):  
Logistic Function ◽  
The Impact ◽  
Passenger Terminals ◽  
Cruise Lines

scholarly journals Technique to study the impact of large herbivores on woody vegetation within piospheres

Koedoe ◽  
2000 ◽  
Vol 43 (2) ◽  
Author(s):  
J. Brits ◽  
M.W. Van Rooyen ◽  
N. Van Rooyen
Keyword(s):  
Soil Type ◽  
Environmental Heterogeneity ◽  
Original Data ◽  
Logistic Function ◽  
Woody Vegetation ◽  
Large Herbivores ◽  
Structural Variables ◽  
Interval Sampling ◽  
The Impact ◽  
Made In

A continuously sampled transect away from a watering point provides good results in situations where geology and soil type remain constant, but is unsuitable to apply where regular changes in soil type occur. A comparison was made between a continuously sampled transect and sampling taken at intervals along the transect. An analysis of variance indicated no significant differences in any of the variables obtained by means of the two sampling methods. The advantage of interval sampling is that, within each zone, areas with the same soil type can be selected in order to avoid environmental heterogeneity. A comparison between transects made in different directions from the watering point yielded no significant differences in any of the structural variables of the woody vegetation at the same distance from the watering point. Therefore, combining transects from different directions to attain a representative sample away from the watering point was an acceptable practice. It is recommended that the original data be smoothed and the logistic function used to model the impact of large herbivores on the structure of the woody vegetation around watering points.

Forecasting the fiber penetration based on copper access regulation

Info ◽  
2014 ◽  
Vol 16 (1) ◽  
pp. 17-31
Author(s):  
François Jeanjean
Keyword(s):  
Negative Impact ◽  
Logistic Function ◽  
Point Of View ◽  
Cable Modem ◽  
Broadband Access ◽  
Content Type ◽  
Access Regulation ◽  
Access Charges ◽  
The Impact ◽  
Practical Implications

Purpose – This paper aims to investigate the impact of copper access regulation on broadband household adoption for each technology (xDSL on copper infrastructure, FTTx on fiber infrastructure and cable modem). It provides a forecast of the penetration rate of broadband access for each technology (copper xDSL, fiber, FTTx and cable modem) through 2020. Design/methodology/approach – This paper uses an empirical approach using a dataset covering 15 European countries. The dynamic of the adoption path is modeled by a logistic function. Copper access regulation is measured by two variables: copper access charge and copper wholesale access share, i.e. the ratio of copper wholesale access provided by the incumbent to alternative operators out of the total number of copper accesses. Findings – This paper shows that tough copper access regulation has a negative impact on fiber and cable modem adoption. Low copper prices decrease consumer adoption of other technologies. This reduces their profitability and thus the incentives to invest in alternative platforms. Practical implications – This paper highlights that an increase in copper access charges or a decrease in copper wholesale access shares could help to achieve the objectives of the Digital Agenda for Europe. Originality/value – This paper provides an empirical evidence of the impact of the copper access regulation on the fiber and ultra-fast broadband adoption from a dynamic point of view.

scholarly journals Impact of Defending Strategy Decision on DDoS Attack

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chunming Zhang
Keyword(s):  
Denial Of Service ◽  
Logistic Function ◽  
Parameter Analysis ◽  
Attack Behavior ◽  
Strategy Selection ◽  
Ddos Attacks ◽  
Effective Strategies ◽  
Ddos Attack ◽  
Existence And Stability ◽  
The Impact

Distributed denial-of-service (DDoS) attack is a serious threat to cybersecurity. Many strategies used to defend against DDoS attacks have been proposed recently. To study the impact of defense strategy selection on DDoS attack behavior, the current study uses logistic function as basis to propose a dynamic model of DDoS attacks with defending strategy decisions. Thereafter, the attacked threshold of this model is calculated. The existence and stability of attack-free and attacked equilibria are proved. Lastly, some effective strategies to mitigate DDoS attacks are suggested through parameter analysis.

scholarly journals Validity Of Scoring Methods In The Presence Of Outliers

2011 ◽  
Vol 6 (11) ◽  
Author(s):  
Nicole Uhde
Keyword(s):  
Extreme Values ◽  
Logistic Function ◽  
Optimal Choice ◽  
Scoring Methods ◽  
Font Size ◽  
Scoring Method ◽  
Heritage Foundation ◽  
Data Points ◽  
Ranking Order ◽  
The Impact

<p class="MsoCommentText" style="margin: 0in 0.5in 0pt;"><span style="font-family: Times New Roman;"><span style="font-size: 10pt; mso-ansi-language: EN-US;">Rankings enjoy growing popularity in the economical sciences. Well known institutions like the World Economic Forum, Heritage Foundation and the OECD make use of rankings to exert competitive pressure on the ranked countries. </span><span style="font-size: 10pt; mso-ansi-language: EN-GB;" lang="EN-GB">To achieve any such desired effects rankings need to be accepted and approved as a whole, and in particular regarding the applied methodology.</span><span style="font-size: 10pt; mso-ansi-language: EN-US;" lang="EN-GB"> </span><span style="font-size: 10pt; mso-ansi-language: EN-US;">In order to appeal to wide sections of the population scoring methods are applied to aggregate a composite indicator. Experience has shown that outliers have a distorting effect on the ranking order and therefore cause economically implausible results which are a target for criticism. For these reasons the choice of an adequate scoring method is of great importance. The applied technique should </span><span style="font-size: 10pt; mso-ansi-language: EN-GB;" lang="EN-GB">provide a feature which enables it to mitigate the distorting effect of outliers </span><span style="font-size: 10pt; mso-ansi-language: EN-US;">without the necessity for an arbitrarily elimination of data points. Although scoring methods have a high influence on ranking results, scientific analysis is often more concerned with the optimal choice of indicators or the weighting scheme, whereas the impact of extreme values is not addressed. According to this, the present research is related to the question which scoring method is the best choice in the presence of outliers. Evidence is given, that Logistic Function Methods have the ability to mitigate outlier distortion effects. The analysis </span><span style="font-size: 10pt; mso-ansi-language: EN-GB;" lang="EN-GB">approaches the issue considering two aspects:</span><span style="font-size: 10pt; mso-ansi-language: EN-US;"> It combines the theoretically derivation of scoring methods&rsquo; statistic strengths and weaknesses for the ranking process and highlights the bootstrap technique to assess the validity of score results in the presence of outliers. </span></span></p>

scholarly journals An Overview of the World Current and Future Assessment of Novel COVID-19 Trajectory, Impact, and Potential Preventive Strategies at Healthcare Settings

2020 ◽  
Vol 17 (19) ◽  
pp. 7016 ◽  
Author(s):  
Bader S. Al-Anzi ◽  
Mohammad Alenizi ◽  
Jehad Al Dallal ◽  
Frage Lhadi Abookleesh ◽  
Aman Ullah
Keyword(s):  
Exponential Model ◽  
Logistic Function ◽  
Continuous Increase ◽  
Future Assessment ◽  
The World ◽  
The Usa ◽  
Group A ◽  
The State Of Kuwait ◽  
Group B ◽  
The Impact

This study is an overview of the current and future trajectory, as well as the impact of the novel Coronavirus (COVID-19) in the world and selected countries including the state of Kuwait. The selected countries were divided into two groups: Group A (China, Switzerland, and Ireland) and Group B (USA, Brazil, and India) based on their outbreak containment of this virus. Then, the actual data for each country were fitted to a regression model utilizing the excel solver software to assess the current and future trajectory of novel COVID-19 and its impact. In addition, the data were fitted using the Susceptible–Infected–Recovered (SIR) Model. The Group A trajectory showed an “S” shape trend that suited a logistic function with r2 > 0.97, which is an indication of the outbreak control. The SIR models for the countries in this group showed that they passed the expected 99% end of pandemic dates. Group B, however, exhibited a continuous increase of the total COVID-19 new cases, that best suited an exponential growth model with r2 > 0.97, which meant that the outbreak is still uncontrolled. The SIR models for the countries in this group showed that they are still relatively far away from reaching the expected 97% end of pandemic dates. The maximum death percentage varied from 3.3% (India) to 7.2% with USA recording the highest death percentage, which is virtually equal to the maximum death percentage of the world (7.3%). The power of the exponential model determines the severity of the country’s trajectory that ranged from 11 to 19 with the USA and Brazil having the highest values. The maximum impact of this COVID-19 pandemic occurred during the uncontrolled stage (2), which mainly depended on the deceptive stage (1). Further, some novel potential containment strategies are discussed. Results from both models showed that the Group A countries contained the outbreak, whereas the Group B countries still have not reached this stage yet. Early measures and containment strategies are imperative in suppressing the spread of COVID-19.

Severity Model Based Prediction of Early Trend and Pattern Recognition of the COVID-19 Infection in India: Exploratory Data Analysis and Machine Learning Study (Preprint)

2020 ◽  
Author(s):  
Afreen Khan ◽  
Swaleha Zubair
Keyword(s):  
Machine Learning ◽  
Growth Rate ◽  
Data Analysis ◽  
Inflection Point ◽  
Exploratory Data Analysis ◽  
Logistic Function ◽  
Acute Stage ◽  
The Future ◽  
Exploratory Data ◽  
The Impact

UNSTRUCTURED Objective: Recent Coronavirus Disease 2019 (COVID-19) pandemic has inflicted the whole world critically. Despite the fact that India has not been listed amongst the top ten highly affected countries, one cannot rule out COVID-19 associated complications in the near future. The accumulative testing facilities has resulted in exponential increase in COVID-19 infection cases. In figures, the number of positive cases have risen up to 33,614 as of 30 April, 2020. Keeping into consideration the serious consequences of pandemic, we aim to establish correlations between the numerous features which was acquired from the various Indian-based COVID datasets, and the impact of the containment of the pandemic on the current state of Indian population using machine learning approach. We aim to build the COVID-19 severity model employing logistic function which determines the inflection point and help in prediction of the future number of confirmed cases. Methods: An empirical study was performed on the COVID-19 patient status in India. We performed the study commencing from 30 January, 2020 to 30 April, 2020 for the analysis. We applied the machine learning (ML) approach to gain the insights about COVID-19 incidences in India. Several diverse exploratory data analysis ML tools and techniques were applied to establish a correlation amongst the various features. Also, the acute stage of the disease was mapped in order to build a robust model. Results: We collected five different datasets to execute the study. The data sets were integrated extract the essential details. We found that men were more prone to get infected of the coronavirus disease as compared to women. Also, the age group was the middle-young age of patients. On 92-days based analysis, we found a trending pattern of number of confirmed, recovered, deceased and active cases of COVID-19 in India. The as-developed growth model provided an inflection point of 85.0 days. It also predicted the number of confirmed cases as 48,958.0 in the future i.e. after 30th April. Growth rate of 13.06 percent was obtained. We achieved statistically significant correlations amongst growth rate and predicted COVID-19 confirmed cases. Conclusion: This study demonstrated the effective application of exploratory data analysis and machine learning in building a mathematical severity model for COVID-19 in India.

scholarly journals Should hunting mortality mimic the patterns of natural mortality?

2008 ◽  
Vol 4 (3) ◽  
pp. 307-310 ◽  
Author(s):  
Richard Bischof ◽  
Atle Mysterud ◽  
Jon E Swenson
Keyword(s):  
Natural Populations ◽  
Logistic Function ◽  
Stochastic Simulations ◽  
Natural Mortality ◽  
Harvest Management ◽  
Biological Trait ◽  
Management Objectives ◽  
Single Strategy ◽  
Harvest Regimes ◽  
The Impact

With growing concerns about the impact of selective harvesting on natural populations, researchers encourage managers to implement harvest regimes that avoid or minimize the potential for demographic and evolutionary side effects. A seemingly intuitive recommendation is to implement harvest regimes that mimic natural mortality patterns. Using stochastic simulations based on a model of risk as a logistic function of a normally distributed biological trait variable, we evaluate the validity of this recommendation when the objective is to minimize the altering effect of harvest on the immediate post-mortality distribution of the trait. We show that, in the absence of compensatory mortality, harvest mimicking natural mortality leads to amplification of the biasing effect expected after natural mortality, whereas an unbiased harvest does not alter the post-mortality trait distribution that would be expected in the absence of harvest. Although our approach focuses only on a subset of many possible objectives for harvest management, it illustrates that a single strategy, such as hunting mimicking natural mortality, may be insufficient to address the complexities of different management objectives with potentially conflicting solutions.

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