Cyber Awareness Exercises: Virtual vs On-site Participation & the Hybrid Approach

2021 ◽  
Vol 10 (2) ◽  
pp. 31-36
Author(s):  
Alexandros ZACHARIS ◽  
Eloise JABES ◽  
Ifigenia LELLA ◽  
Evangelos REKLEITIS
Keyword(s):  
Statistical Analysis ◽  
Social Interaction ◽  
Success Factors ◽  
Hybrid Approach ◽  
Advantages And Disadvantages ◽  
Cyber Threats ◽  
Diverse Data ◽  
Exercise Design ◽  
Near Future

This paper examines the advantages and disadvantages of executing cyber awareness exercises in two different formats: Virtual vs On-site participation. Two EU Agencies, EUSPA and ENISA have organized in the previous years Cyber Awareness exercises; a very important tool to enhance and test the organization's ability to put up resistance and respond to different cyber threats. The objective of this paper is to compare the outcomes of these awareness exercises, executed on-site through physical attendance prior to 2019 and virtually, in a remote setup in 2020, due to the restrictions posed by the pandemic of COVID-19. ENISA in collaboration with EUSPA have accumulated raw and diverse data from the evaluation reports of the cyber events mentioned above. The comparison of these data will focus on the most important success factors of a cyber awareness exercise such as: participation, cooperation (social interaction/teambuilding), effectiveness, fun, tools and identify how the location of the participants affects them. The aim of this work is to highlight through statistical analysis the benefits of a hybrid approach to the exercise’s setup, once combining elements of both virtual and on-site. Depending on the different kind of exercises, such a hybrid setup, will provide more flexibility to an exercise organizer and help maximize effectiveness, while adapting to the fluctuating working regimes of the near future; namely Teleworking. Furthermore, a modular exercise design will be proposed in order to adapt to the location limitations without impacting negatively the rate of the rest of factors analyzed.

Methods

2020 ◽  
pp. 109-145
Author(s):  
Ulrich Frey
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Statistical Analysis ◽  
Random Forests ◽  
Success Factors ◽  
Indicator System ◽  
Advantages And Disadvantages ◽  
Quantitative Measurements ◽  
Ecological Success ◽  
Statistical Analysis Methods

The three statistical analysis methods used are presented: multivariate linear regression, random forests, and artificial neural networks. Their respective advantages and disadvantages are discussed as well as how they can complement each other. Using three independent methods increases the robustness of results considerably. A further subchapter describes the operationalization of success factors through the development of an indicator system. Particular attention is paid to the validation of this system through external experts, its practical use, and operationalization of ecological success. Different ways of operationalizing ecological success are compared for forests. The surprising conclusion is that experts’ judgment is equivalent to expensive quantitative measurements.

scholarly journals A Siamese neural network model for the prioritization of metabolic disorders by integrating real and simulated data

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i787-i794
Author(s):  
Gian Marco Messa ◽  
Francesco Napolitano ◽  
Sarah H. Elsea ◽  
Diego di Bernardo ◽  
Xin Gao
Keyword(s):  
Predictive Accuracy ◽  
Hybrid Approach ◽  
Simulated Data ◽  
Original Data ◽  
Diagnostic Process ◽  
Great Promise ◽  
Metabolic Profiles ◽  
Inborn Errors ◽  
Metabolomic Data ◽  
Near Future

Abstract Motivation Untargeted metabolomic approaches hold a great promise as a diagnostic tool for inborn errors of metabolisms (IEMs) in the near future. However, the complexity of the involved data makes its application difficult and time consuming. Computational approaches, such as metabolic network simulations and machine learning, could significantly help to exploit metabolomic data to aid the diagnostic process. While the former suffers from limited predictive accuracy, the latter is normally able to generalize only to IEMs for which sufficient data are available. Here, we propose a hybrid approach that exploits the best of both worlds by building a mapping between simulated and real metabolic data through a novel method based on Siamese neural networks (SNN). Results The proposed SNN model is able to perform disease prioritization for the metabolic profiles of IEM patients even for diseases that it was not trained to identify. To the best of our knowledge, this has not been attempted before. The developed model is able to significantly outperform a baseline model that relies on metabolic simulations only. The prioritization performances demonstrate the feasibility of the method, suggesting that the integration of metabolic models and data could significantly aid the IEM diagnosis process in the near future. Availability and implementation Metabolic datasets used in this study are publicly available from the cited sources. The original data produced in this study, including the trained models and the simulated metabolic profiles, are also publicly available (Messa et al., 2020).

scholarly journals Hybrid Neuro-Fractal Analysis of ECG Signals to Predict Ischemia

2021 ◽  
Author(s):  
Hedieh Montazeri
Keyword(s):  
Neural Network ◽  
Logistic Regression ◽  
Statistical Analysis ◽  
Linear Regression ◽  
Fractal Analysis ◽  
Prediction Accuracy ◽  
Clinical Characteristics ◽  
Hybrid Approach ◽  
Binary Logistic Regression ◽  
Ecg Signals

In this thesis, we propose and implement a new hybrid approach using fractal analysis, statistical analysis and neural network computation to build a model for prediction the number of ischemia occurrence based on ECG recordings. The main advantage of the proposed approach over similar earlier related works is that first useful parameters from fractal analysis of the signal are extracted to build a model that includes both clinical characteristics and signal attributes. Statistical analysis such as binary logistic regression and multivariate linear regression are then used to further explore the relation of parameters in order to obtain a more accurate model. We show that the results compare well with those of earlier work and clearly indicate that the augmentation of the above mentioned approaches improves the prediction accuracy.

Outdoor Seating Design to Facilitate Social Interaction Among Older Adults

2009 ◽  
Vol 17 (4) ◽  
pp. 4-27 ◽  
Author(s):  
Thamar Swart ◽  
Johan Molenbroek ◽  
Lau Langeveld ◽  
Martin Van Brederode ◽  
Brecht J. Daams
Keyword(s):  
Older Adults ◽  
Social Interaction ◽  
The Netherlands ◽  
Design Process ◽  
Literature Search ◽  
Public Spaces ◽  
Usability Test ◽  
Public Meeting ◽  
Near Future

AT A GLANCE: The number of older adults who like to meet each other in public spaces in the Netherlands is increasing. For this article, older adults were surveyed regarding their wants and needs for public meeting spaces. By means of a literature search on ergonomics, interviews, observations, and discussions with experts and older adults, a list of needs and preferences was created and used to guide a design for an outdoor meeting space for older adults, dubbed “The Oud-door.” Older adults were engaged in the design process by asking them questions, discussing the ideas and concepts with them, and, finally, conducting a usability test. Manufacturer Jan Kuipers Nunspeet will develop this design further, and “The Oud-door” will be available on the market in the near future.

WSBen

2011 ◽  
pp. 739-758 ◽  
Author(s):  
Seog-Chan Oh ◽  
Dongwon Lee
Keyword(s):  
Statistical Analysis ◽  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Network Models ◽  
Web Service Composition ◽  
Ai Planning ◽  
Underlying Network ◽  
Test Sets ◽  
Diverse Data

In this article, a novel benchmark toolkit, WSBen, for testing web services discovery and composition algorithms is presented. The WSBen includes: (1) a collection of synthetically generated web services files in WSDL format with diverse data and model characteristics; (2) queries for testing discovery and composition algorithms; (3) auxiliary files to do statistical analysis on the WSDL test sets; (4) converted WSDL test sets that conventional AI planners can read; and (5) a graphical interface to control all these behaviors. Users can finetune the generated WSDL test files by varying underlying network models. To illustrate the application of the WSBen, in addition, we present case studies from three domains: (1) web service composition; (2) AI planning; and (3) the laws of networks in Physics community. It is our hope that WSBen will provide useful insights in evaluating the performance of web services discovery and composition algorithms. The WSBen toolkit is available at: http://pike.psu.edu/sw/wsben/.

Role of Molecular Docking in Computer-Aided Drug Design and Development

2016 ◽  
pp. 1-28
Author(s):  
Rahul Agarwal ◽  
Ashutosh Singh ◽  
Subhabrata Sen
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Protein Binding ◽  
Design And Development ◽  
Advantages And Disadvantages ◽  
Computer Aided ◽  
Drug Designing ◽  
Near Future

Molecular Docking is widely used in CADD (Computer-Aided Drug Designing), SBDD (Structure-Based Drug Designing) and LBDD (Ligand-Based Drug Designing). It is a method used to predict the binding orientation of one molecule with the other and used for any kind of molecule based on the interaction like, small drug molecule with its protein target, protein – protein binding or a DNA – protein binding. Docking is very much popular technique due to its reliable prediction properties. This book chapter will provide an overview of diverse docking methodologies present that are used in drug design and development. There will be discussion on several case studies, pertaining to each method, followed by advantages and disadvantages of the discussed methodology. It will typically aim professionals in the field of cheminformatics and bioinformatics, both in academia and in industry and aspiring scientists and students who want to take up this as a profession in the near future. We will conclude with our opinion on the effectiveness of this technology in the future of pharmaceutical industry.

A Hybrid Technique Using PCA and Wavelets in Network Traffic Anomaly Detection

2014 ◽  
Vol 6 (1) ◽  
pp. 17-53 ◽  
Author(s):  
Stevan Novakov ◽  
Chung-Horng Lung ◽  
Ioannis Lambadaris ◽  
Nabil Seddigh
Keyword(s):  
Spectral Analysis ◽  
Statistical Analysis ◽  
Wavelet Analysis ◽  
Anomaly Detection ◽  
Network Traffic ◽  
Hybrid Approach ◽  
Haar Wavelet ◽  
Wavelet Filtering ◽  
Analysis Technique ◽  
Network Anomaly Detection

Research into network anomaly detection has become crucial as a result of a significant increase in the number of computer attacks. Many approaches in network anomaly detection have been reported in the literature, but data or solutions typically are not freely available. Recently, a labeled network traffic flow dataset, Kyoto2006+, has been created and is publicly available. Most existing approaches using Kyoto2006+ for network anomaly detection apply various clustering techniques. This paper leverages existing well known statistical analysis and spectral analysis techniques for network anomaly detection. The first popular approach is a statistical analysis technique called Principal Component Analysis (PCA). PCA describes data in a new dimension to unlock otherwise hidden characteristics. The other well known spectral analysis technique is Haar Wavelet filtering analysis. It measures the amount and magnitude of abrupt changes in data. Both approaches have strengths and limitations. In response, this paper proposes a Hybrid PCA–Haar Wavelet Analysis. The hybrid approach first applies PCA to describe the data and then Haar Wavelet filtering for analysis. Based on prototyping and measurement, an investigation of the Hybrid PCA–Haar Wavelet Analysis technique is performed using the Kyoto2006+ dataset. The authors consider a number of parameters and present experimental results to demonstrate the effectiveness of the hybrid approach as compared to the two algorithms individually.

scholarly journals Work Ethics and Social Responsibility: Actual and Aspiration

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Ali Awad Alwagfi ◽  
Nader Mohammad Aljawarneh ◽  
Khaled Abdalqader Alomari
Keyword(s):  
Statistical Analysis ◽  
Social Responsibility ◽  
Business Organizations ◽  
Educational Organizations ◽  
Male And Female ◽  
Work Ethics ◽  
Advantages And Disadvantages ◽  
The Social ◽  
Descriptive Approach

This study aims at investigating the reality of social responsibility, and its ethical dimensions in educational business organizations in addition to knowing the prevailing advantages and disadvantages. The sample of the study consisted of northern Jordanian universities were 210 male and female as respondents to a questionnaire. 200 questionnaires were valid for statistical analysis in order to achieve the purposes of this study; the researcher adopted a descriptive approach. This study utilized a tool to measure the social responsibility, and its ethical dimensions in private northern Jordanian universities. The study concluded that the correlation between social responsibility and ethical dimensions were statistically significant. In light of the aforementioned findings, the study recommended the raising employees’ morals and motivating them in ethical ways, in addition to developing a clear plan applied by educational organizations to apply and practice social responsibility.

scholarly journals Comparison of oil press for jatropha oil – a review

2016 ◽  
Vol 61 (No. 1) ◽  
pp. 1-13 ◽  
Author(s):  
A.N. Siregar ◽  
J.A. Ghani ◽  
C.H.C. Haron ◽  
M. Rizal ◽  
Z. Yaakob ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Oil Extraction ◽  
Biodiesel Production ◽  
South East Asia ◽  
Jatropha Oil ◽  
Extraction Techniques ◽  
Advantages And Disadvantages ◽  
Jatropha Seeds ◽  
Mechanical Extraction ◽  
Near Future

As petrol will soon be exhausted in the near future, Jatropha is going to be one of the substitute candidates for future biodiesel production. Countries of South-East Asia, such as Malaysia, they are going to start the establishment of Jatropha plantations assuming that Jatropha will be the main resource for biodiesel production. A press is commonly used to extract oils from Jatropha. An oil press can be manually driven or engine-powered. In this paper, we will review some available advances focused on mechanical extraction techniques, covering three types of press for Jatropha oil extraction. We have found that major points like operating principles, oil extraction levels, advantages and disadvantages of each press and important factors to increase oil recovery. Based on the study, three types of press are: ram press, which is ineffective; strainer press, which is able to produce more oil than others and cylinder-hole press, which is the best due to its capacity in extracting oil from Jatropha seeds for about 89.4% of oil yields.

The Problem of Multiple Inference in Psychiatric Research

1985 ◽  
Vol 19 (3) ◽  
pp. 265-274 ◽  
Author(s):  
Wayne Hall ◽  
Kevin Bird
Keyword(s):  
Statistical Analysis ◽  
Statistical Inference ◽  
Multivariate Statistical Analysis ◽  
Research Study ◽  
Psychiatric Research ◽  
Exploratory Research ◽  
Multivariate Statistical ◽  
Advantages And Disadvantages ◽  
Multivariate Study ◽  
Study Designs

This paper deals with the problem of multiple inference in psychiatric research, an issue which arises whenever a researcher has to make more than one statistical inference in a single research study. It frequently arises in psychiatric research because of multivariate study designs, with subjects being measured on more than one dependent variable with the intention of studying differences between groups in mean scores. The disadvantages of the commonly adopted strategy of using multiple univariate tests (e.g. multiple t-tests) are outlined. Two broad strategies — Bonferroni-adjusted univariate tests and multivariate statistical analysis — are introduced. Their advantages and disadvantages are discussed in terms of their usefulness in confirmatory and exploratory research in psychiatry.

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