scholarly journals Matching Cyber Security Ontologies through Genetic Algorithm-Based Ontology Alignment Technique

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Weiwei Lin ◽  
Reiko Haga
Keyword(s):  
Genetic Algorithm ◽  
Cyber Security ◽  
Shared Knowledge ◽  
Ontology Alignment ◽  
Knowledge Model ◽  
Semantic Relationships ◽  
Advantages And Disadvantages ◽  
Data Heterogeneity ◽  
Alignment Technique

Security ontology can be used to build a shared knowledge model for an application domain to overcome the data heterogeneity issue, but it suffers from its own heterogeneity issue. Finding identical entities in two ontologies, i.e., ontology alignment, is a solution. It is important to select an effective similarity measure (SM) to distinguish heterogeneous entities. However, due to the complex semantic relationships among concepts, no SM is ensured to be effective in all alignment tasks. The aggregation of SMs so that their advantages and disadvantages complement each other directly affects the quality of alignments. In this work, we formally define this problem, discuss its challenges, and present a problem-specific genetic algorithm (GA) to effectively address it. We experimentally test our approach on bibliographic tracks provided by OAEI and five pairs of security ontologies. The results show that GA can effectively address different heterogeneous ontology-alignment tasks and determine high-quality security ontology alignments.

Impact of Big Data on Security

2018 ◽  
pp. 283-299 ◽  
Author(s):  
Ramgopal Kashyap ◽  
Albert D. Piersson
Keyword(s):  
Big Data ◽  
Cyber Security ◽  
Privacy Preservation ◽  
Big Data Analytics ◽  
Security Issue ◽  
Social Media Data ◽  
Advantages And Disadvantages ◽  
Data Heterogeneity ◽  
Types Of Information ◽  
Media Data

The motivation behind this chapter is to highlight the qualities, security issue, advantages, and disadvantages of big data. In the recent researches, the issue and challenges are due to the exponential growth of social media data and other images and videos. Big data security threats are rising, which is affecting the data heterogeneity adaptability and privacy preservation analytics. Big data analytics helps cyber security, but no new application can be envisioned without delivering new types of information, working on data-driven calculations and expending determined measure of information. This chapter demonstrates how innate attributes of big data are protected.

scholarly journals Genetic Algorithm with New Stochastic Greedy Crossover Operator for Protein Structure Folding Problem

2020 ◽  
pp. 19-29
Author(s):  
Leonid Hulianytskyi ◽  
Sergii Chornozhuk
Keyword(s):  
Genetic Algorithm ◽  
Free Energy ◽  
Protein Structure ◽  
Combinatorial Optimization ◽  
Global Minimum ◽  
Optimal Algorithm ◽  
Crossover Operator ◽  
Actual Problem ◽  
Advantages And Disadvantages

Introduction. The spatial protein structure folding is an important and actual problem in biology. Considering the mathematical model of the task, we can conclude that it comes down to the combinatorial optimization problem. Therefore, genetic and mimetic algorithms can be used to find a solution. The article proposes a genetic algorithm with a new greedy stochastic crossover operator, which differs from classical approaches with paying attention to qualities of possible ancestors. The purpose of the article is to describe a genetic algorithm with a new greedy stochastic crossover operator, reveal its advantages and disadvantages, compare the proposed algorithm with the best-known implementations of genetic and memetic algorithms for the spatial protein structure prediction, and make conclusions with future steps suggestion afterward. Result. The work of the proposed algorithm is compared with others on the basis of 10 known chains with a length of 48 first proposed in [13]. For each of the chain, a global minimum of free energy was already precalculated. The algorithm found 9 out of 10 spatial structures on which a global minimum of free energy is achieved and also demonstrated a better average value of solutions than the comparing algorithms. Conclusion. The quality of the genetic algorithm with the greedy stochastic crossover operator has been experimentally confirmed. Consequently, its further research is promising. For example, research on the selection of optimal algorithm parameters, improving the speed and quality of solutions found through alternative coding or parallelization. Also, it is worth testing the proposed algorithm on datasets with proteins of other lengths for further checks of the algorithm’s validity. Keywords: spatial protein structure, combinatorial optimization, genetic algorithms, crossover operator, stochasticity.

scholarly journals Investigation of the Possibility of Applying a Genetic Algorithm for Electroacoustics Problems

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Artem Dmytrovych Zubkov ◽  
Denys Dmytrovych Volkov ◽  
Vitalii Semenovych Didkovkyi
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Classical Method ◽  
Fitness Function ◽  
Added Mass ◽  
Mathematical Representation ◽  
Advantages And Disadvantages ◽  
Electroacoustic Transducer ◽  
Representation Of Solutions

This paper considers the adaptation and application of a genetic algorithm to find the parameters of the electrodynamic transducer model. The advantages and disadvantages of this method in comparison with the classical method of identification using added mass are considered. The derivation of the suitability function for estimating the identified parameters is presented, which can also be used to identify other types of electroacoustic transducers. The theory underlying genetic algorithms has been examined and shown how genetic algorithms work by assembling the best solutions from small structural elements with excellent qualities. Next, the differences between genetic and traditional algorithms were analyzed, including population population support and the use of genetic representation of solutions. After that, the strengths of genetic algorithms were described, including the possibility of global optimization and applicability to problems with complex mathematical representation or without representation at all, and noise resistance. Disadvantages were also highlighted: the need for special definitions and settings of hyperparameters, the danger of premature convergence. In conclusion, the situations when the use of genetic algorithms are listed This algorithm is not tied to a specific engineering or scientific field, which makes it universal, it is equally used in genetics and computer science. The parameters were determined using a genetic algorithm and compared with the more classical method of added mass for acoustics. The comparative table in the work illustrates the high accuracy of the genetic algorithm in comparison with the method of added mass. During the work on the practical part, also to improve the behavior of the model at frequencies higher than the resonant, it was decided to complicate the model of the electrical subsystem of the tranducer and introduce additional parameters: parallel resistance and parallel inductance. As a result, the complicated model began to correspond better to the measured values   in the entire frequency domain, and is therefore more accurate. This is an example of the convenience of using a genetic algorithm in the transition from identification of one model with specific parameters to another. The results of this work prove that the use of a genetic algorithm is appropriate for solving electroacoustic problems because its application allows to quickly experiment and identify more complex models for which the added mass method can not be applied. Also, in the future, genetic algorithm can be used to identify transducer models of in time domain, for example, nonlinear models of electrodynamic transducers or models in a state space, which is the subject of future research.This paper considers the adaptation and application of a genetic algorithm to find the parameters of the electrodynamic transducer model. The advantages and disadvantages of this method in comparison with the classical method of identification using added mass and the method of parameter selection BL are considered. The derivation of the fitness function for assessing the quality of the identified parameters is presented, which can also be used to identify other types of electroacoustic transducers. The directly measured values ​​for the application of the algorithm are the voltage at the terminals of the converter, the current through the coil of the converter and the displacement of the moving part of the converter. The undoubted advantage of the genetic algorithm compared to classical identification methods is its versatility and the ability to quickly adapt and configure for research and experimentation with different models and different types of transducers used in acoustics. This article describes the adaptation and application of a genetic algorithm to find parameters of an electrodynamic transducer model. The advantages and disadvantages of this method in comparison with the classical identification method using added mass are considered. The derivation of the fitness function for assessing quality of the identified parameters is presented, which can also be used to identify other types of electroacoustic transducer models.

Can trust become a factor of economic growth? Dynamic changes in the level of trust of Russian youth

2020 ◽  
pp. 92-107 ◽  
Author(s):  
A. I. Bakhtigaraeva ◽  
A. A. Stavinskaya
Keyword(s):  
Institutional Environment ◽  
Negative Effects ◽  
Dynamic Changes ◽  
Generalized Trust ◽  
Level Of Education ◽  
Advantages And Disadvantages ◽  
The Future ◽  
Analysis Of Dynamics

The article considers the role of trust in the economy, the mechanisms of its accumulation and the possibility of using it as one of the growth factors in the future. The advantages and disadvantages of measuring the level of generalized trust using two alternative questions — about trusting people in general and trusting strangers — are analyzed. The results of the analysis of dynamics of the level of generalized trust among Russian youth, obtained within the study of the Institute for National Projects in 10 regions of Russia, are presented. It is shown that there are no significant changes in trust in people in general during the study at university. At the same time, the level of trust in strangers falls, which can negatively affect the level of trust in the country as a whole, and as a result have negative effects on the development of the economy in the future. Possible causes of the observed trends and the role of universities are discussed. Also the question about the connection between the level of education and generalized trust in countries with different quality of the institutional environment is raised.

Data Integrity Techniques in Cloud Computing: An Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 121 ◽  
Author(s):  
Neha Thakur ◽  
Aman Kumar Sharma
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Data Integrity ◽  
Advantages And Disadvantages ◽  
Security Models ◽  
Cloud Storage Service ◽  
Storage Service ◽  
Cloud Users ◽  
It Enterprises

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record.  In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.

Problems of Distance Education

2018 ◽  
Vol 7 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Rostislav Fojtík
Keyword(s):  
Distance Education ◽  
Distance Learning ◽  
Computer Science ◽  
Full Time ◽  
Advantages And Disadvantages ◽  
E Learning ◽  
Educational Requirements

Abstract Distance learning and e-learning have significantly developed in recent years. It is also due to changing educational requirements, especially for adults. The article aims to show the advantages and disadvantages of distance learning. Examples of the 20-year use of the distance learning form of computer science describe the difficulties associated with the implementation and implementation of this form of teaching. The results of students in the full-time and distance form of teaching in the bachelor’s study of computer science are compared. Long-term findings show that distant students have significantly lower scores in the first years of study than full-time bachelor students. In the following years of study, the differences diminish, and students’ results are comparable. The article describes the possibilities of improving the quality of distance learning.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals Systematic Analysis of Literature on the Marketing of Healthcare Systems. Challenges for Russian and Romanian Healthcare Systems

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 656
Author(s):  
Vladimir Bulatnikov ◽  
Cristinel Petrişor Constantin
Keyword(s):  
Quality Of Healthcare ◽  
Healthcare Systems ◽  
Business Environment ◽  
Competitive Advantages ◽  
Systematic Analysis ◽  
Scientific Databases ◽  
Advantages And Disadvantages ◽  
Funds Allocation ◽  
New Perspective

This paper aims at finding the most dominant ideas about the marketing of healthcare systems highlighted in the mainstream literature, with a focus on Russia and Romania. To reach this goal, a systematic analysis of literature was conducted and various competitive advantages and disadvantages of the medical models that require special attention from the governments are considered. In this respect we examined 106 papers published during 2006 to 2020 found on four scientific databases. They were selected using inclusion and exclusion criteria according to PRISMA methodology. The main findings of the research consist of the opportunity to use marketing tools in order to improve the quality of healthcare systems in the named countries. Thus, using market orientation, the managers of healthcare systems could stimulate the innovation, the efficiency of funds allocation and the quality of medical services. The results will lead to a better quality of population life and to an increasing of life expectancy. As this paper reviews some articles from Russian literature, it can add a new perspective to the topic. These outcomes have implications for government, business environment, and academia, which should cooperate in order to develop the healthcare system using marketing strategies.

scholarly journals Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6401
Author(s):  
Kateryna Czerniachowska ◽  
Karina Sachpazidu-Wójcicka ◽  
Piotr Sulikowski ◽  
Marcin Hernes ◽  
Artur Rot
Keyword(s):  
Genetic Algorithm ◽  
Profit Maximization ◽  
Allocation Rule ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Shelf Space Allocation ◽  
To Receive

This paper discusses the problem of retailers’ profit maximization regarding displaying products on the planogram shelves, which may have different dimensions in each store but allocate the same product sets. We develop a mathematical model and a genetic algorithm for solving the shelf space allocation problem with the criteria of retailers’ profit maximization. The implemented program executes in a reasonable time. The quality of the genetic algorithm has been evaluated using the CPLEX solver. We determine four groups of constraints for the products that should be allocated on a shelf: shelf constraints, shelf type constraints, product constraints, and virtual segment constraints. The validity of the developed genetic algorithm has been checked on 25 retailing test cases. Computational results prove that the proposed approach allows for obtaining efficient results in short running time, and the developed complex shelf space allocation model, which considers multiple attributes of a shelf, segment, and product, as well as product capping and nesting allocation rule, is of high practical relevance. The proposed approach allows retailers to receive higher store profits with regard to the actual merchandising rules.

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