Rivista e Edizione

Volume 22 (2022): Edizione 3 (September 2022)

Volume 22 (2022): Edizione 2 (June 2022)

Volume 22 (2022): Edizione 1 (March 2022)

Volume 21 (2021): Edizione 4 (December 2021)

Volume 21 (2021): Edizione 3 (September 2021)

Volume 21 (2021): Edizione 2 (June 2021)

Volume 21 (2021): Edizione 1 (March 2021)

Volume 20 (2020): Edizione 6 (December 2020)
Special Edizione on New Developments in Scalable Computing

Volume 20 (2020): Edizione 5 (December 2020)
Special issue on Innovations in Intelligent Systems and Applications

Volume 20 (2020): Edizione 4 (November 2020)

Volume 20 (2020): Edizione 3 (September 2020)

Volume 20 (2020): Edizione 2 (June 2020)

Volume 20 (2020): Edizione 1 (March 2020)

Volume 19 (2019): Edizione 4 (November 2019)

Volume 19 (2019): Edizione 3 (September 2019)

Volume 19 (2019): Edizione 2 (June 2019)

Volume 19 (2019): Edizione 1 (March 2019)

Volume 18 (2018): Edizione 5 (May 2018)
Special Thematic Edizione on Optimal Codes and Related Topics

Volume 18 (2018): Edizione 4 (November 2018)

Volume 18 (2018): Edizione 3 (September 2018)

Volume 18 (2018): Edizione 2 (June 2018)

Volume 18 (2018): Edizione 1 (March 2018)

Volume 17 (2017): Edizione 5 (December 2017)
Special Edizione With Selected Papers From The Workshop “Two Years Avitohol: Advanced High Performance Computing Applications 2017

Volume 17 (2017): Edizione 4 (November 2017)

Volume 17 (2017): Edizione 3 (September 2017)

Volume 17 (2017): Edizione 2 (June 2017)

Volume 17 (2017): Edizione 1 (March 2017)

Volume 16 (2016): Edizione 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

Volume 16 (2016): Edizione 5 (October 2016)
Edizione Title: Special Edizione on Application of Advanced Computing and Simulation in Information Systems

Volume 16 (2016): Edizione 4 (December 2016)

Volume 16 (2016): Edizione 3 (September 2016)

Volume 16 (2016): Edizione 2 (June 2016)

Volume 16 (2016): Edizione 1 (March 2016)

Volume 15 (2015): Edizione 7 (December 2015)
Special Edizione on Information Fusion

Volume 15 (2015): Edizione 6 (December 2015)
Special Edizione on Logistics, Informatics and Service Science

Volume 15 (2015): Edizione 5 (April 2015)
Special Edizione on Control in Transportation Systems

Volume 15 (2015): Edizione 4 (November 2015)

Volume 15 (2015): Edizione 3 (September 2015)

Volume 15 (2015): Edizione 2 (June 2015)

Volume 15 (2015): Edizione 1 (March 2015)

Volume 14 (2014): Edizione 5 (December 2014)
Special Edizione

Volume 14 (2014): Edizione 4 (December 2014)

Volume 14 (2014): Edizione 3 (September 2014)

Volume 14 (2014): Edizione 2 (June 2014)

Volume 14 (2014): Edizione 1 (March 2014)

Volume 13 (2013): Edizione Special-Edizione (December 2013)

Volume 13 (2013): Edizione 4 (December 2013)
The publishing of the present issue (Volume 13, No 4, 2013) of the journal “Cybernetics and Information Technologies” is financially supported by FP7 project “Advanced Computing for Innovation” (ACOMIN), grant agreement 316087 of Call FP7 REGPOT-2012-2013-1.

Volume 13 (2013): Edizione 3 (September 2013)

Volume 13 (2013): Edizione 2 (June 2013)

Volume 13 (2013): Edizione 1 (March 2013)

Volume 12 (2012): Edizione 4 (December 2012)

Volume 12 (2012): Edizione 3 (September 2012)

Volume 12 (2012): Edizione 2 (June 2012)

Volume 12 (2012): Edizione 1 (March 2012)

Dettagli della rivista
Formato
Rivista
eISSN
1314-4081
Pubblicato per la prima volta
13 Mar 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

Volume 21 (2021): Edizione 2 (June 2021)

Dettagli della rivista
Formato
Rivista
eISSN
1314-4081
Pubblicato per la prima volta
13 Mar 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

12 Articoli
Accesso libero

Some Properties Related to Reduct of Consistent Decision Systems

Pubblicato online: 01 Jul 2021
Pagine: 3 - 9

Astratto

Abstract

Reduct of decision systems is the topic that has been attracting the interest of many researchers in data mining and machine learning for more than two decades. So far, many algorithms for finding reduct of decision systems by rough set theory have been proposed. However, most of the proposed algorithms are heuristic algorithms that find one reduct with the best classification quality. The complete study of properties of reduct of decision systems is limited. In this paper, we discover equivalence properties of reduct of consistent decision systems related to a Sperner-system. As the result, the study of the family of reducts in a consistent decision system is the study of Sperner-systems.

Parole chiave

  • Relational database
  • rough set theory
  • Sperner-system
  • decision system
  • reduct
Accesso libero

A New Noisy Random Forest Based Method for Feature Selection

Pubblicato online: 01 Jul 2021
Pagine: 10 - 28

Astratto

Abstract

Feature selection is an essential pre-processing step in data mining. It aims at identifying the highly predictive feature subset out of a large set of candidate features. Several approaches for feature selection have been proposed in the literature. Random Forests (RF) are among the most used machine learning algorithms not just for their excellent prediction accuracy but also for their ability to select informative variables with their associated variable importance measures. Sometimes RF model over-fits on noisy features, which lead to choosing the noisy features as the informative variables and eliminating the significant ones. Whereas, eliminating and preventing those noisy features first, the low ranked features may become more important. In this study we propose a new variant of RF that provides unbiased variable selection where a noisy feature trick is used to address this problem. First, we add a noisy feature to a dataset. Second, the noisy feature is used as a stopping criterion. If the noisy feature is selected as the best splitting feature, then we stop the creation process because at this level, the model starts to over-fit on the noisy features. Finally, the best subset of features is selected out of the best-ranked feature regarding the Geni impurity of this new variant of RF. To test the validity and the effectiveness of the proposed method, we compare it with RF variable importance measure using eleven benchmarking datasets.

Parole chiave

  • Feature selection
  • data mining
  • random forest
  • Geni impurity
  • variable importance
Accesso libero

Fuzzy-Logic Based Active Queue Management Using Performance Metrics Mapping into Multi-Congestion Indicators

Pubblicato online: 01 Jul 2021
Pagine: 29 - 44

Astratto

Abstract

The congestion problem at the router buffer leads to serious consequences on network performance. Active Queue Management (AQM) has been developed to react to any possible congestion at the router buffer at an early stage. The limitation of the existing fuzzy-based AQM is the utilization of indicators that do not address all the performance criteria and quality of services required. In this paper, a new method for active queue management is proposed based on using the fuzzy logic and multiple performance indicators that are extracted from the network performance metrics. These indicators are queue length, delta queue and expected loss. The simulation of the proposed method show that in high traffic load, the proposed method preserves packet loss, drop packet only when it is necessary and produce a satisfactory delay that outperformed the state-of-the-art AQM methods.

Parole chiave

  • Congestion control
  • network performance
  • active queue management
  • fuzzy logic
Accesso libero

Performance Evaluation of Change Detection in SAR Images Based on Hybrid Antlion DWT Fuzzy c-Means Clustering

Pubblicato online: 01 Jul 2021
Pagine: 45 - 57

Astratto

Abstract

In this paper, the main objective is to detect changes in the geographical area of Ottawa city in Canada due to floods. Two multi-temporal Synthetic Aperture Radar (SAR) images have been taken to evaluate the un-supervised change detection process. In this process, two ratio operators named as Log-Ratio and Mean-Ratio are used to generate a difference image. Performing image fusion based on DWT by selecting optimum filter coefficients by satisfying the wavelet filter coefficient properties through a novel image fusion technique is named as ADWT. GA, PSO, AntLion Optimization algorithms (ALO) and Hybridized AntLion Algorithm (HALO) have been adapted to perform the ADWT based image fusion. Segmentation has been performed based on fuzzy c-Means clustering to detect changed and unchanged pixels. Finally, the performance of the proposed method will be analysed by comparing the segmented image with the ground truth image in terms of sensitivity, accuracy, specificity, precision, F1-score.

Parole chiave

  • ADWT
  • ALO Algorithm
  • HALO Algorithm
  • GA Algorithm
  • PSO Algorithm
Accesso libero

A Recursive and Parallelized Dynamic Programming Implementation of Hard Merkle-Hellman Knapsack System for Public Key Cryptography

Pubblicato online: 01 Jul 2021
Pagine: 58 - 69

Astratto

Abstract

Merkle-Hellman public key cryptosystem is a long-age old algorithm used in cryptography. Despite being computationally fast, for very large input sizes it may operate slower due to thread creation overhead or reaching a deadlock situation. In this paper, we discuss the working principles of the Traditional Merkle-Hellman knapsack cryptosystem, which is an Easy knapsack. The challenges of Hard Knapsack and how it overcomes the shortcomings of the Traditional Easy Knapsack, are also discussed. The Hard knapsack variant of Merkle-Hellman is solved first using plain recursion and then improvised using a dynamic programming approach to the problem. Parallelism and Concurrency has been achieved on the dynamic programming implementation using OpenMP API which further has enhanced the performance time. A comparative study of both variants of Hard Knapsack for messages of different lengths has shown that the latter is faster.

Parole chiave

  • Merkle-Hellman public key cryptosystem
  • Easy knapsack
  • Hard knapsack
  • recursion
  • dynamic programming
  • parallelism
  • OpenMP API
Accesso libero

Computation of Trusted Short Weierstrass Elliptic Curves for Cryptography

Pubblicato online: 01 Jul 2021
Pagine: 70 - 88

Astratto

Abstract

Short Weierstrass elliptic curves with underlying hard Elliptic Curve Discrete Logarithm Problem (ECDLP) are widely used in cryptographic applications. A notion of security called Elliptic Curve Cryptography (ECC) security is also suggested in literature to safeguard the elliptic curve cryptosystems from their implementation flaws. In this paper, a new security notion called the “trusted security” is introduced for computational method of elliptic curves for cryptography. We propose three additional “trusted security acceptance criteria” which need to be met by the elliptic curves aimed for cryptography. Further, two cryptographically secure elliptic curves over 256 bit and 384 bit prime fields are demonstrated which are secure from ECDLP, ECC as well as trust perspectives. The proposed elliptic curves are successfully subjected to thorough security analysis and performance evaluation with respect to key generation and signing/verification and hence, proven for their cryptographic suitability and great feasibility for acceptance by the community.

Parole chiave

  • Short Weierstrass elliptic curves
  • prime field
  • cryptography
  • ECDLP Security
  • ECC Security
  • Trusted Security
Accesso libero

A New Digital Image Steganography Based on Center Embedded Pixel Positioning

Pubblicato online: 01 Jul 2021
Pagine: 89 - 104

Astratto

Abstract

In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

Parole chiave

  • Cover image
  • cropping
  • security
  • stego image
  • steganography
Accesso libero

An Enhanced Semantic Focused Web Crawler Based on Hybrid String Matching Algorithm

Pubblicato online: 01 Jul 2021
Pagine: 105 - 120

Astratto

Abstract

Topic precise crawler is a special purpose web crawler, which downloads appropriate web pages analogous to a particular topic by measuring cosine similarity or semantic similarity score. The cosine based similarity measure displays inaccurate relevance score, if topic term does not directly occur in the web page. The semantic-based similarity measure provides the precise relevance score, even if the synonyms of the given topic occur in the web page. The unavailability of the topic in the ontology produces inaccurate relevance score by the semantic focused crawlers. This paper overcomes these glitches with a hybrid string-matching algorithm by combining the semantic similarity-based measure with the probabilistic similarity-based measure. The experimental results revealed that this algorithm increased the efficiency of the focused web crawlers and achieved better Harvest Rate (HR), Precision (P) and Irrelevance Ratio (IR) than the existing web focused crawlers achieve.

Parole chiave

  • Probabilistic model
  • hybrid semantic similarity
  • web focused crawler
  • string matching
Accesso libero

A Model for e-Learning Based on the Knowledge of Learners

Pubblicato online: 01 Jul 2021
Pagine: 121 - 135

Astratto

Abstract

The presented work examines the existing approaches to providing e-Learning content based on learners’ prior knowledge. An analysis of the existing tools for the development of e-Learning content is performed and their suitability for creating personalized learning content, reflecting the previous competencies of the learners, is carried out. In the paper we have used a step-by-step process of creating and providing personalized knowledge. For data analysis, an approach of describing small structural units of knowledge through competencies is used. As a result of our study we have proposed a conceptual model including interactive resources for analysis of the accumulated prior knowledge and tools for providing personalized content to the learners. Perspective directions for future work are also outlined.

Parole chiave

  • Personalized e-Learning
  • authoring tools
  • lifelong learning
  • e-Learning content development
  • prior knowledge analysis
Accesso libero

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

Pubblicato online: 01 Jul 2021
Pagine: 136 - 165

Astratto

Abstract

Wireless networks play an important role in science, including medicine, agriculture, the military, geography, and so on. The main issue with a network of wireless sensors is how to manage resource utilization to extend its lifetime. This paper investigates the various aspects of increased energy usage that may improve network life. Variables related to energy consumption and various performance metrics are investigated in terms of energy efficiency. To investigate how the network’s energy usage can be managed, a quick overview of clustering protocols, routing protocols, MAC protocols, and load balancing protocols is conducted. This paper can provide researchers with an idea of the various parameters that influence energy consumption and what methodologies could be adapted by each parameter to conserve energy, thereby extending the network’s lifetime.

Parole chiave

  • Energy
  • clustering
  • routing
  • MAC
  • duty cycle
  • load balancing
Accesso libero

An IRGA-MACS Based Cluster-Head Selection Protocol for Wireless Sensor Networks

Pubblicato online: 01 Jul 2021
Pagine: 166 - 182

Astratto

Abstract

In a volatile environment, a substantial number of sensor nodes are extensively dispatched to track and detect changes in physical environment. Although sensor nodes have limited energy resources, so energy-efficient routing is a major concern in Wireless Sensor Networks (WSN) to extend the network’s lifespan. Recent research shows that less throughput, increased delay, and high execution time have been provided with high energy usage. A new mechanism called the IRGA-MACS is proposed to overcome these inherent problems. Firstly, the Improved Resampling Genetic Algorithm (IRGA) is used for the best Cluster Head (CH) selection. Secondly, to assess the shortest path among CHs and nodes, the Modified Ant Colony Optimization based Simulated Annealing (MACS) has been speculated to minimize the time consumption during the transmission. The results show that the proposed approaches attain the supreme goal of increasing the network lifetime compared to existing methods.

Parole chiave

  • WSN
  • IRGA-MACS
  • resampling
  • CH selection
  • energy efficiency
Accesso libero

A Centralized Model Enabling Channel Reuse for Spectrum Allocation in Cognitive Radio Networks

Pubblicato online: 01 Jul 2021
Pagine: 183 - 200

Astratto

Abstract

Cognitive Radio (CR) is an advanced technology, which intends to boost the radio spectrum utilization. On perceiving the spectrum holes, next there is a need to provide a fair distribution of the vacant licensed channels amongst Secondary Users (SUs) during the spectrum allocation process. In this context, our paper introduces two allocation models to resolve the spectrum allocation problem. Initially, we design a simple centralized model to assign the channels. Then, we extend it to a centralized fair allocation model that aims to impart a better utilization of the free channels. Both approaches assign a common channel to a group of non-interfering SUs simultaneously. This facilitates spectrum reuse. The constraint related to dynamics in spectrum opportunities in CR is handled during channel allocation. Simulation study analyzes the proposed approaches with an existing allocation mechanism and reveals the performance improvement of centralized fair allocation model in terms of spectrum utilization.

Parole chiave

  • Cognitive radio
  • dynamic spectrum access
  • spectrum allocation
  • spectrum opportunities
  • channel reuse
12 Articoli
Accesso libero

Some Properties Related to Reduct of Consistent Decision Systems

Pubblicato online: 01 Jul 2021
Pagine: 3 - 9

Astratto

Abstract

Reduct of decision systems is the topic that has been attracting the interest of many researchers in data mining and machine learning for more than two decades. So far, many algorithms for finding reduct of decision systems by rough set theory have been proposed. However, most of the proposed algorithms are heuristic algorithms that find one reduct with the best classification quality. The complete study of properties of reduct of decision systems is limited. In this paper, we discover equivalence properties of reduct of consistent decision systems related to a Sperner-system. As the result, the study of the family of reducts in a consistent decision system is the study of Sperner-systems.

Parole chiave

  • Relational database
  • rough set theory
  • Sperner-system
  • decision system
  • reduct
Accesso libero

A New Noisy Random Forest Based Method for Feature Selection

Pubblicato online: 01 Jul 2021
Pagine: 10 - 28

Astratto

Abstract

Feature selection is an essential pre-processing step in data mining. It aims at identifying the highly predictive feature subset out of a large set of candidate features. Several approaches for feature selection have been proposed in the literature. Random Forests (RF) are among the most used machine learning algorithms not just for their excellent prediction accuracy but also for their ability to select informative variables with their associated variable importance measures. Sometimes RF model over-fits on noisy features, which lead to choosing the noisy features as the informative variables and eliminating the significant ones. Whereas, eliminating and preventing those noisy features first, the low ranked features may become more important. In this study we propose a new variant of RF that provides unbiased variable selection where a noisy feature trick is used to address this problem. First, we add a noisy feature to a dataset. Second, the noisy feature is used as a stopping criterion. If the noisy feature is selected as the best splitting feature, then we stop the creation process because at this level, the model starts to over-fit on the noisy features. Finally, the best subset of features is selected out of the best-ranked feature regarding the Geni impurity of this new variant of RF. To test the validity and the effectiveness of the proposed method, we compare it with RF variable importance measure using eleven benchmarking datasets.

Parole chiave

  • Feature selection
  • data mining
  • random forest
  • Geni impurity
  • variable importance
Accesso libero

Fuzzy-Logic Based Active Queue Management Using Performance Metrics Mapping into Multi-Congestion Indicators

Pubblicato online: 01 Jul 2021
Pagine: 29 - 44

Astratto

Abstract

The congestion problem at the router buffer leads to serious consequences on network performance. Active Queue Management (AQM) has been developed to react to any possible congestion at the router buffer at an early stage. The limitation of the existing fuzzy-based AQM is the utilization of indicators that do not address all the performance criteria and quality of services required. In this paper, a new method for active queue management is proposed based on using the fuzzy logic and multiple performance indicators that are extracted from the network performance metrics. These indicators are queue length, delta queue and expected loss. The simulation of the proposed method show that in high traffic load, the proposed method preserves packet loss, drop packet only when it is necessary and produce a satisfactory delay that outperformed the state-of-the-art AQM methods.

Parole chiave

  • Congestion control
  • network performance
  • active queue management
  • fuzzy logic
Accesso libero

Performance Evaluation of Change Detection in SAR Images Based on Hybrid Antlion DWT Fuzzy c-Means Clustering

Pubblicato online: 01 Jul 2021
Pagine: 45 - 57

Astratto

Abstract

In this paper, the main objective is to detect changes in the geographical area of Ottawa city in Canada due to floods. Two multi-temporal Synthetic Aperture Radar (SAR) images have been taken to evaluate the un-supervised change detection process. In this process, two ratio operators named as Log-Ratio and Mean-Ratio are used to generate a difference image. Performing image fusion based on DWT by selecting optimum filter coefficients by satisfying the wavelet filter coefficient properties through a novel image fusion technique is named as ADWT. GA, PSO, AntLion Optimization algorithms (ALO) and Hybridized AntLion Algorithm (HALO) have been adapted to perform the ADWT based image fusion. Segmentation has been performed based on fuzzy c-Means clustering to detect changed and unchanged pixels. Finally, the performance of the proposed method will be analysed by comparing the segmented image with the ground truth image in terms of sensitivity, accuracy, specificity, precision, F1-score.

Parole chiave

  • ADWT
  • ALO Algorithm
  • HALO Algorithm
  • GA Algorithm
  • PSO Algorithm
Accesso libero

A Recursive and Parallelized Dynamic Programming Implementation of Hard Merkle-Hellman Knapsack System for Public Key Cryptography

Pubblicato online: 01 Jul 2021
Pagine: 58 - 69

Astratto

Abstract

Merkle-Hellman public key cryptosystem is a long-age old algorithm used in cryptography. Despite being computationally fast, for very large input sizes it may operate slower due to thread creation overhead or reaching a deadlock situation. In this paper, we discuss the working principles of the Traditional Merkle-Hellman knapsack cryptosystem, which is an Easy knapsack. The challenges of Hard Knapsack and how it overcomes the shortcomings of the Traditional Easy Knapsack, are also discussed. The Hard knapsack variant of Merkle-Hellman is solved first using plain recursion and then improvised using a dynamic programming approach to the problem. Parallelism and Concurrency has been achieved on the dynamic programming implementation using OpenMP API which further has enhanced the performance time. A comparative study of both variants of Hard Knapsack for messages of different lengths has shown that the latter is faster.

Parole chiave

  • Merkle-Hellman public key cryptosystem
  • Easy knapsack
  • Hard knapsack
  • recursion
  • dynamic programming
  • parallelism
  • OpenMP API
Accesso libero

Computation of Trusted Short Weierstrass Elliptic Curves for Cryptography

Pubblicato online: 01 Jul 2021
Pagine: 70 - 88

Astratto

Abstract

Short Weierstrass elliptic curves with underlying hard Elliptic Curve Discrete Logarithm Problem (ECDLP) are widely used in cryptographic applications. A notion of security called Elliptic Curve Cryptography (ECC) security is also suggested in literature to safeguard the elliptic curve cryptosystems from their implementation flaws. In this paper, a new security notion called the “trusted security” is introduced for computational method of elliptic curves for cryptography. We propose three additional “trusted security acceptance criteria” which need to be met by the elliptic curves aimed for cryptography. Further, two cryptographically secure elliptic curves over 256 bit and 384 bit prime fields are demonstrated which are secure from ECDLP, ECC as well as trust perspectives. The proposed elliptic curves are successfully subjected to thorough security analysis and performance evaluation with respect to key generation and signing/verification and hence, proven for their cryptographic suitability and great feasibility for acceptance by the community.

Parole chiave

  • Short Weierstrass elliptic curves
  • prime field
  • cryptography
  • ECDLP Security
  • ECC Security
  • Trusted Security
Accesso libero

A New Digital Image Steganography Based on Center Embedded Pixel Positioning

Pubblicato online: 01 Jul 2021
Pagine: 89 - 104

Astratto

Abstract

In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

Parole chiave

  • Cover image
  • cropping
  • security
  • stego image
  • steganography
Accesso libero

An Enhanced Semantic Focused Web Crawler Based on Hybrid String Matching Algorithm

Pubblicato online: 01 Jul 2021
Pagine: 105 - 120

Astratto

Abstract

Topic precise crawler is a special purpose web crawler, which downloads appropriate web pages analogous to a particular topic by measuring cosine similarity or semantic similarity score. The cosine based similarity measure displays inaccurate relevance score, if topic term does not directly occur in the web page. The semantic-based similarity measure provides the precise relevance score, even if the synonyms of the given topic occur in the web page. The unavailability of the topic in the ontology produces inaccurate relevance score by the semantic focused crawlers. This paper overcomes these glitches with a hybrid string-matching algorithm by combining the semantic similarity-based measure with the probabilistic similarity-based measure. The experimental results revealed that this algorithm increased the efficiency of the focused web crawlers and achieved better Harvest Rate (HR), Precision (P) and Irrelevance Ratio (IR) than the existing web focused crawlers achieve.

Parole chiave

  • Probabilistic model
  • hybrid semantic similarity
  • web focused crawler
  • string matching
Accesso libero

A Model for e-Learning Based on the Knowledge of Learners

Pubblicato online: 01 Jul 2021
Pagine: 121 - 135

Astratto

Abstract

The presented work examines the existing approaches to providing e-Learning content based on learners’ prior knowledge. An analysis of the existing tools for the development of e-Learning content is performed and their suitability for creating personalized learning content, reflecting the previous competencies of the learners, is carried out. In the paper we have used a step-by-step process of creating and providing personalized knowledge. For data analysis, an approach of describing small structural units of knowledge through competencies is used. As a result of our study we have proposed a conceptual model including interactive resources for analysis of the accumulated prior knowledge and tools for providing personalized content to the learners. Perspective directions for future work are also outlined.

Parole chiave

  • Personalized e-Learning
  • authoring tools
  • lifelong learning
  • e-Learning content development
  • prior knowledge analysis
Accesso libero

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

Pubblicato online: 01 Jul 2021
Pagine: 136 - 165

Astratto

Abstract

Wireless networks play an important role in science, including medicine, agriculture, the military, geography, and so on. The main issue with a network of wireless sensors is how to manage resource utilization to extend its lifetime. This paper investigates the various aspects of increased energy usage that may improve network life. Variables related to energy consumption and various performance metrics are investigated in terms of energy efficiency. To investigate how the network’s energy usage can be managed, a quick overview of clustering protocols, routing protocols, MAC protocols, and load balancing protocols is conducted. This paper can provide researchers with an idea of the various parameters that influence energy consumption and what methodologies could be adapted by each parameter to conserve energy, thereby extending the network’s lifetime.

Parole chiave

  • Energy
  • clustering
  • routing
  • MAC
  • duty cycle
  • load balancing
Accesso libero

An IRGA-MACS Based Cluster-Head Selection Protocol for Wireless Sensor Networks

Pubblicato online: 01 Jul 2021
Pagine: 166 - 182

Astratto

Abstract

In a volatile environment, a substantial number of sensor nodes are extensively dispatched to track and detect changes in physical environment. Although sensor nodes have limited energy resources, so energy-efficient routing is a major concern in Wireless Sensor Networks (WSN) to extend the network’s lifespan. Recent research shows that less throughput, increased delay, and high execution time have been provided with high energy usage. A new mechanism called the IRGA-MACS is proposed to overcome these inherent problems. Firstly, the Improved Resampling Genetic Algorithm (IRGA) is used for the best Cluster Head (CH) selection. Secondly, to assess the shortest path among CHs and nodes, the Modified Ant Colony Optimization based Simulated Annealing (MACS) has been speculated to minimize the time consumption during the transmission. The results show that the proposed approaches attain the supreme goal of increasing the network lifetime compared to existing methods.

Parole chiave

  • WSN
  • IRGA-MACS
  • resampling
  • CH selection
  • energy efficiency
Accesso libero

A Centralized Model Enabling Channel Reuse for Spectrum Allocation in Cognitive Radio Networks

Pubblicato online: 01 Jul 2021
Pagine: 183 - 200

Astratto

Abstract

Cognitive Radio (CR) is an advanced technology, which intends to boost the radio spectrum utilization. On perceiving the spectrum holes, next there is a need to provide a fair distribution of the vacant licensed channels amongst Secondary Users (SUs) during the spectrum allocation process. In this context, our paper introduces two allocation models to resolve the spectrum allocation problem. Initially, we design a simple centralized model to assign the channels. Then, we extend it to a centralized fair allocation model that aims to impart a better utilization of the free channels. Both approaches assign a common channel to a group of non-interfering SUs simultaneously. This facilitates spectrum reuse. The constraint related to dynamics in spectrum opportunities in CR is handled during channel allocation. Simulation study analyzes the proposed approaches with an existing allocation mechanism and reveals the performance improvement of centralized fair allocation model in terms of spectrum utilization.

Parole chiave

  • Cognitive radio
  • dynamic spectrum access
  • spectrum allocation
  • spectrum opportunities
  • channel reuse

Pianifica la tua conferenza remota con Sciendo