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Volumen 21 (2021): Heft 2 (June 2021)

Volumen 21 (2021): Heft 1 (March 2021)

Volumen 20 (2020): Heft 6 (December 2020)
Special Heft on New Developments in Scalable Computing

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

Volumen 20 (2020): Heft 4 (November 2020)

Volumen 20 (2020): Heft 3 (September 2020)

Volumen 20 (2020): Heft 2 (June 2020)

Volumen 20 (2020): Heft 1 (March 2020)

Volumen 19 (2019): Heft 4 (November 2019)

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Volumen 19 (2019): Heft 2 (June 2019)

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Special Thematic Heft on Optimal Codes and Related Topics

Volumen 18 (2018): Heft 4 (November 2018)

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

Volumen 17 (2017): Heft 4 (November 2017)

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Volumen 17 (2017): Heft 2 (June 2017)

Volumen 17 (2017): Heft 1 (March 2017)

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

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

Volumen 16 (2016): Heft 4 (December 2016)

Volumen 16 (2016): Heft 3 (September 2016)

Volumen 16 (2016): Heft 2 (June 2016)

Volumen 16 (2016): Heft 1 (March 2016)

Volumen 15 (2015): Heft 7 (December 2015)
Special Heft on Information Fusion

Volumen 15 (2015): Heft 6 (December 2015)
Special Heft on Logistics, Informatics and Service Science

Volumen 15 (2015): Heft 5 (April 2015)
Special Heft on Control in Transportation Systems

Volumen 15 (2015): Heft 4 (November 2015)

Volumen 15 (2015): Heft 3 (September 2015)

Volumen 15 (2015): Heft 2 (June 2015)

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Volumen 14 (2014): Heft 5 (December 2014)
Special Heft

Volumen 14 (2014): Heft 4 (December 2014)

Volumen 14 (2014): Heft 3 (September 2014)

Volumen 14 (2014): Heft 2 (June 2014)

Volumen 14 (2014): Heft 1 (March 2014)

Volumen 13 (2013): Heft Special-Heft (December 2013)

Volumen 13 (2013): Heft 4 (December 2013)
The publishing of the present issue (Volumen 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.

Volumen 13 (2013): Heft 3 (September 2013)

Volumen 13 (2013): Heft 2 (June 2013)

Volumen 13 (2013): Heft 1 (March 2013)

Volumen 12 (2012): Heft 4 (December 2012)

Volumen 12 (2012): Heft 3 (September 2012)

Volumen 12 (2012): Heft 2 (June 2012)

Volumen 12 (2012): Heft 1 (March 2012)

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 20 (2020): Heft 4 (November 2020)

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

11 Artikel
Uneingeschränkter Zugang

Localization in Wireless Sensor Networks: A Review

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 3 - 26

Zusammenfassung

Abstract

Wireless Sensor Network (WSN) has been a source of attraction for many researchers as well as common people for the past few years. The use of WSN in various environmental applications like monitoring of weather, temperature, humidity, military surveillance etc. is not limited. WSN is built on hundreds to thousands of nodes where each node is a sensor whose main role is to sense data. These nodes are restricted to various constraints like power, energy, efficiency and deployment. The location of deployment influences the efficiency of data transmission. In this paper we briefly discuss on localization process in WSN and the classification of localization methodologies, namely centralized localization and distributed localization. The various techniques like ToA, TDoA, AoA and RSSI that are used to estimate the distance among the nodes are studied in detail. The localization issues categorized under proximity-based, range-based and range-free localization are discussed in detail. This paper also focuses on how the nodes with GPS can contribute to the localization process. The merits and demerits of using GPS have also been looked into. The various approaches of range-based techniques like Bounding box, SumDistMinMax, geometric methods, general techniques have been discussed briefly. We will also discuss on how the factors like path loss, noise, propagation, device measurements, connectivity, power control and tracking can influence the measurements in localization. In the tracking process we have briefly discussed about the variants of Kalman filter that can be used in detecting the direct path, strongest path and undirected path. This paper as a whole is just a brush up of the localization methodologies used in wireless sensor networks. This paper may give idea to the researchers to develop efficient algorithms to localize nodes with accuracy adapting to different techniques with respect to the environment and applications to be designed.

Schlüsselwörter

  • Localization
  • TOA
  • TDOA
  • path loss
  • noise
  • multipath
  • WSN
Uneingeschränkter Zugang

A Novel Alternative Algorithm for Solving Integer Linear Programming Problems Having Three Variables

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 27 - 35

Zusammenfassung

Abstract

In this study, a novel alternative method based on parameterization for solving Integer Linear Programming (ILP) problems having three variables is developed. This method, which is better than the cutting plane and branch boundary method, can be applied to pure integer linear programming problems with m linear inequality constraints, a linear objective function with three variables. Both easy to understand and to apply, the method provides an effective tool for solving three variable integer linear programming problems. The method proposed here is not only easy to understand and apply, it is also highly reliable, and there are no computational difficulties faced by other methods used to solve the three-variable pure integer linear programming problem. Numerical examples are provided to demonstrate the ease, effectiveness and reliability of the proposed algorithm.

Schlüsselwörter

  • Linear Integer Programming (LIP)
  • linear Diophantine equations
  • optimal hyperplane
  • pure integer programming problems
  • optimal solution
Uneingeschränkter Zugang

On the Usability of Object-Oriented Design Patterns for a Better Software Quality

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 36 - 54

Zusammenfassung

Abstract

Software design patterns incarnate expert knowledge distilled from the practical experience in object-oriented design, in a compact and reusable form. The article presents a quantitative study of the usability of the object-oriented software design patterns (known as Gang of Four patterns) applied for improving the testability, maintainability, extendibility, readability, reliability, and performance efficiency of software applications. We received 82 usable responses from software professionals in Bulgaria, with 65 of them addressing both the usability and recognition of each one of the Gang of Four patterns, together with their impact on important software quality characteristics. As well, we studied the approach of each software developer in choosing a particular design pattern to use in order to solve a problem. We found statistically significant differences between the most recognized and most useful patterns and between the most unrecognized and most useless patterns, split into creational, structural, and behavioral groups.

Schlüsselwörter

  • Design patterns
  • usability
  • software quality
  • survey
Uneingeschränkter Zugang

HPCWMF: A Hybrid Predictive Cloud Workload Management Framework Using Improved LSTM Neural Network

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 55 - 73

Zusammenfassung

Abstract

For cloud providers, workload prediction is a challenging task due to irregular incoming workloads from users. Accurate workload prediction is essential for scheduling the resources to the cloud applications. Thus, in this paper, the authors propose a predictive cloud workload management framework to estimate the needed resources in advance based on a hybrid approach, which is a combination of an improved Long Short-Term Memory (LSTM) network and a multilayer perceptron network. By improving the traditional LSTM architecture by using opposition-based differential evolution algorithm and dropout technique on recurrent connection without memory loss, the proposed approach has the ability to perform a better prediction process. A novel hybrid predictive approach is aiming at enhancing the prediction performance of the cloud workload. Finally, the authors measure the proposed approach’s effectiveness under benchmark data sets of NASA and Saskatchewan servers. The experimental results proved that the proposed approach outperforms the other conventional methods.

Schlüsselwörter

  • Cloud computing
  • Improved LSTM neural network
  • Multilayer perceptron network
  • Opposition-based differential evolution
  • Workload prediction
Uneingeschränkter Zugang

Face Authenticated Hand Gesture Based Human Computer Interaction for Desktops

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 74 - 89

Zusammenfassung

Abstract

Hand gesture detection and recognition is a cutting-edge technology that is getting progressively applicable in several applications, including the recent trends namely Virtual Reality and Augmented Reality. It is a key part of Human-Computer Interaction which gives an approach to two-way interaction between the computer and the user. Currently, this technology is limited to expensive and highly specialized equipment and gadgets such as Kinect and the Oculus Rift. In this paper, various technologies and methodologies of implementing a gesture detection and recognition system are discussed. The paper also includes the implementation of a face recognition module using the Viola-Jones Algorithm for authentication of the system followed by hand gesture recognition using CNN to perform basic operations on the laptop. Any type of user can use gesture control as an alternative and interesting way to control their laptop. Furthermore, this can be used as a prototype for future implementations in the field of virtual reality as well as augmented reality.

Schlüsselwörter

  • Gesture recognition
  • gesture detection
  • human-computer interaction
  • Haar-cascade
  • convolution neural network
  • Viola-Jones Algorithm
  • ReLU activation
  • convolutional layer
  • max-pooling
  • k-Gaussian distribution
Uneingeschränkter Zugang

All-words Word Sense Disambiguation for Russian Using Automatically Generated Text Collection

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 90 - 107

Zusammenfassung

Abstract

The limited amount of the sense annotated data is a big challenge for the word sense disambiguation task. As a solution to this problem, we propose an algorithm of automatic generation and labelling of the training collections based on the monosemous relatives concept. In this article we explore the limits of this algorithm: we employ it to harvest training collections for all ambiguous nouns, verbs and adjectives presented in RuWordNet thesaurus and then evaluate the quality of the obtained collections. We demonstrate that our approach can create high-quality labelled collections with almost full-coverage of the RuWordNet polysemous words. Furthermore, we show that our method can be applied to the Word-in-Context task.

Schlüsselwörter

  • Word Sense Disambiguation
  • Word-in-Context task
  • automatic annotation of training collections
  • monosemous relatives
  • Russian dataset
  • RuWordNet thesaurus
Uneingeschränkter Zugang

Towards a Conceptual Description of Verbs

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 108 - 124

Zusammenfassung

Abstract

Our work is focused on the conceptual description of verbs by employing two main resources – the lexical semantic network WordNet and the conceptual frames from FrameNet. We implement a method for inheritance-based mapping between the two resources by transferring the frame assignments from a hypernym to its hyponyms. We discover that the method performs best for directly related pairs of synsets but deteriorates in assignment at two or more steps. The mapping is then used for enhancing each of the resources by expanding it with new entries and by contributing to the resources’ relational structure.

Schlüsselwörter

  • FrameNet
  • WordNet
  • Frame Semantics
  • semantic relations
Uneingeschränkter Zugang

Linguistic vs Encyclopaedic Knowledge. Classification of MWEs from Wikipedia Articles

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 125 - 140

Zusammenfassung

Abstract

This paper reports on the first steps in the creation of linked data through the mapping between the synsets of BTB-WordNet and the articles in Bulgarian Wikipedia. The task of expanding the BTB-WordNet with encyclopaedic knowledge is done by mapping its synsets to Wikipedia articles with many MWEs found in the articles and subjected to further analysis. We look for a way to filter the Wikipedia MWEs in the effort of selecting the ones most beneficial to the enrichment of BTB-WN.

Schlüsselwörter

  • MWEs
  • Wordnet
  • Wikipedia
  • Semantic Mapping
Uneingeschränkter Zugang

Sentiment Analysis of Tweets on Coronavirus Disease 2019 (COVID-19) Pandemic from Metro Manila, Philippines

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 141 - 155

Zusammenfassung

Abstract

From the outbreak of a novel COronaVIrus Disease (COVID-19) in Wuhan to the first COVID-19 case in the Philippines, Filipinos have been enthusiastically engaging on Twitter to convey their sentiments. As such, this paper aims to identify the public opinion of Filipino twitter users concerning COVID-19 in three different timelines. Toward this goal, a total of 65,396 tweets related to COVID-19 were sent to data analysis using R Statistical Software. Results show that “mask”, “health”, “lockdown”, “outbreak”, “test”, “kit”, “university”, “alcohol”, and “suspension” were some of the most frequently occurring words in the tweets. The study further investigates Filipinos’ emotions regarding COVID-19 by calculating text polarity of the dataset. To date, this is the first paper to perform sentiment analysis on tweets pertaining to COVID-19 not only in the Filipino context but worldwide as well.

Schlüsselwörter

  • Sentiment analysis
  • coronavirus disease
  • Philippines
  • Twitter
  • opinion mining
  • COVID-19
  • NCOV
  • virus
  • tweets
  • Data Mining
Uneingeschränkter Zugang

Predictive Analysis of Dengue Outbreak Based on an Improved Salp Swarm Algorithm

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 156 - 169

Zusammenfassung

Abstract

The purpose of this study is to enhance the exploration capability of conventional Salp Swarm Algorithm (SSA) with the inducing of Levy Flight. With such modification, it will assist the SSA from trapping in local optimum. The proposed approach, which is later known as an improved SSA (iSSA) is employed in monthly dengue outbreak prediction. For that matter, monthly dataset of rainfall, humidity, temperature and number of dengue cases were employed, which render prediction information. The efficiency of the proposed algorithm is evaluated using Root Mean Square Error (RMSE), and compared against the conventional SSA and Ant Colony Optimization (ACO). The obtained results suggested that the iSSA was not only able to produce lower RMSE, but also capable to converge faster at lower rate as well.

Schlüsselwörter

  • Dengue outbreak prediction
  • meta-heuristic
  • optimization
  • predictive analysis
  • Salp Swarm Algorithm
  • swarm intelligence
Uneingeschränkter Zugang

Why Perturbations?

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 170 - 175

Zusammenfassung

Abstract

Review on the book M. M. Konstantinov, P. H. Petkov. Perturbation Methods in Matrix Analysis and Control. NOVA Science Publishers, Inc., New York, 2020. ISBN 978-1-53617-470-0. https://novapublishers.com/shop/perturbation-methods-in-matrix-analysis-and-control/

11 Artikel
Uneingeschränkter Zugang

Localization in Wireless Sensor Networks: A Review

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 3 - 26

Zusammenfassung

Abstract

Wireless Sensor Network (WSN) has been a source of attraction for many researchers as well as common people for the past few years. The use of WSN in various environmental applications like monitoring of weather, temperature, humidity, military surveillance etc. is not limited. WSN is built on hundreds to thousands of nodes where each node is a sensor whose main role is to sense data. These nodes are restricted to various constraints like power, energy, efficiency and deployment. The location of deployment influences the efficiency of data transmission. In this paper we briefly discuss on localization process in WSN and the classification of localization methodologies, namely centralized localization and distributed localization. The various techniques like ToA, TDoA, AoA and RSSI that are used to estimate the distance among the nodes are studied in detail. The localization issues categorized under proximity-based, range-based and range-free localization are discussed in detail. This paper also focuses on how the nodes with GPS can contribute to the localization process. The merits and demerits of using GPS have also been looked into. The various approaches of range-based techniques like Bounding box, SumDistMinMax, geometric methods, general techniques have been discussed briefly. We will also discuss on how the factors like path loss, noise, propagation, device measurements, connectivity, power control and tracking can influence the measurements in localization. In the tracking process we have briefly discussed about the variants of Kalman filter that can be used in detecting the direct path, strongest path and undirected path. This paper as a whole is just a brush up of the localization methodologies used in wireless sensor networks. This paper may give idea to the researchers to develop efficient algorithms to localize nodes with accuracy adapting to different techniques with respect to the environment and applications to be designed.

Schlüsselwörter

  • Localization
  • TOA
  • TDOA
  • path loss
  • noise
  • multipath
  • WSN
Uneingeschränkter Zugang

A Novel Alternative Algorithm for Solving Integer Linear Programming Problems Having Three Variables

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 27 - 35

Zusammenfassung

Abstract

In this study, a novel alternative method based on parameterization for solving Integer Linear Programming (ILP) problems having three variables is developed. This method, which is better than the cutting plane and branch boundary method, can be applied to pure integer linear programming problems with m linear inequality constraints, a linear objective function with three variables. Both easy to understand and to apply, the method provides an effective tool for solving three variable integer linear programming problems. The method proposed here is not only easy to understand and apply, it is also highly reliable, and there are no computational difficulties faced by other methods used to solve the three-variable pure integer linear programming problem. Numerical examples are provided to demonstrate the ease, effectiveness and reliability of the proposed algorithm.

Schlüsselwörter

  • Linear Integer Programming (LIP)
  • linear Diophantine equations
  • optimal hyperplane
  • pure integer programming problems
  • optimal solution
Uneingeschränkter Zugang

On the Usability of Object-Oriented Design Patterns for a Better Software Quality

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 36 - 54

Zusammenfassung

Abstract

Software design patterns incarnate expert knowledge distilled from the practical experience in object-oriented design, in a compact and reusable form. The article presents a quantitative study of the usability of the object-oriented software design patterns (known as Gang of Four patterns) applied for improving the testability, maintainability, extendibility, readability, reliability, and performance efficiency of software applications. We received 82 usable responses from software professionals in Bulgaria, with 65 of them addressing both the usability and recognition of each one of the Gang of Four patterns, together with their impact on important software quality characteristics. As well, we studied the approach of each software developer in choosing a particular design pattern to use in order to solve a problem. We found statistically significant differences between the most recognized and most useful patterns and between the most unrecognized and most useless patterns, split into creational, structural, and behavioral groups.

Schlüsselwörter

  • Design patterns
  • usability
  • software quality
  • survey
Uneingeschränkter Zugang

HPCWMF: A Hybrid Predictive Cloud Workload Management Framework Using Improved LSTM Neural Network

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 55 - 73

Zusammenfassung

Abstract

For cloud providers, workload prediction is a challenging task due to irregular incoming workloads from users. Accurate workload prediction is essential for scheduling the resources to the cloud applications. Thus, in this paper, the authors propose a predictive cloud workload management framework to estimate the needed resources in advance based on a hybrid approach, which is a combination of an improved Long Short-Term Memory (LSTM) network and a multilayer perceptron network. By improving the traditional LSTM architecture by using opposition-based differential evolution algorithm and dropout technique on recurrent connection without memory loss, the proposed approach has the ability to perform a better prediction process. A novel hybrid predictive approach is aiming at enhancing the prediction performance of the cloud workload. Finally, the authors measure the proposed approach’s effectiveness under benchmark data sets of NASA and Saskatchewan servers. The experimental results proved that the proposed approach outperforms the other conventional methods.

Schlüsselwörter

  • Cloud computing
  • Improved LSTM neural network
  • Multilayer perceptron network
  • Opposition-based differential evolution
  • Workload prediction
Uneingeschränkter Zugang

Face Authenticated Hand Gesture Based Human Computer Interaction for Desktops

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 74 - 89

Zusammenfassung

Abstract

Hand gesture detection and recognition is a cutting-edge technology that is getting progressively applicable in several applications, including the recent trends namely Virtual Reality and Augmented Reality. It is a key part of Human-Computer Interaction which gives an approach to two-way interaction between the computer and the user. Currently, this technology is limited to expensive and highly specialized equipment and gadgets such as Kinect and the Oculus Rift. In this paper, various technologies and methodologies of implementing a gesture detection and recognition system are discussed. The paper also includes the implementation of a face recognition module using the Viola-Jones Algorithm for authentication of the system followed by hand gesture recognition using CNN to perform basic operations on the laptop. Any type of user can use gesture control as an alternative and interesting way to control their laptop. Furthermore, this can be used as a prototype for future implementations in the field of virtual reality as well as augmented reality.

Schlüsselwörter

  • Gesture recognition
  • gesture detection
  • human-computer interaction
  • Haar-cascade
  • convolution neural network
  • Viola-Jones Algorithm
  • ReLU activation
  • convolutional layer
  • max-pooling
  • k-Gaussian distribution
Uneingeschränkter Zugang

All-words Word Sense Disambiguation for Russian Using Automatically Generated Text Collection

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 90 - 107

Zusammenfassung

Abstract

The limited amount of the sense annotated data is a big challenge for the word sense disambiguation task. As a solution to this problem, we propose an algorithm of automatic generation and labelling of the training collections based on the monosemous relatives concept. In this article we explore the limits of this algorithm: we employ it to harvest training collections for all ambiguous nouns, verbs and adjectives presented in RuWordNet thesaurus and then evaluate the quality of the obtained collections. We demonstrate that our approach can create high-quality labelled collections with almost full-coverage of the RuWordNet polysemous words. Furthermore, we show that our method can be applied to the Word-in-Context task.

Schlüsselwörter

  • Word Sense Disambiguation
  • Word-in-Context task
  • automatic annotation of training collections
  • monosemous relatives
  • Russian dataset
  • RuWordNet thesaurus
Uneingeschränkter Zugang

Towards a Conceptual Description of Verbs

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 108 - 124

Zusammenfassung

Abstract

Our work is focused on the conceptual description of verbs by employing two main resources – the lexical semantic network WordNet and the conceptual frames from FrameNet. We implement a method for inheritance-based mapping between the two resources by transferring the frame assignments from a hypernym to its hyponyms. We discover that the method performs best for directly related pairs of synsets but deteriorates in assignment at two or more steps. The mapping is then used for enhancing each of the resources by expanding it with new entries and by contributing to the resources’ relational structure.

Schlüsselwörter

  • FrameNet
  • WordNet
  • Frame Semantics
  • semantic relations
Uneingeschränkter Zugang

Linguistic vs Encyclopaedic Knowledge. Classification of MWEs from Wikipedia Articles

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 125 - 140

Zusammenfassung

Abstract

This paper reports on the first steps in the creation of linked data through the mapping between the synsets of BTB-WordNet and the articles in Bulgarian Wikipedia. The task of expanding the BTB-WordNet with encyclopaedic knowledge is done by mapping its synsets to Wikipedia articles with many MWEs found in the articles and subjected to further analysis. We look for a way to filter the Wikipedia MWEs in the effort of selecting the ones most beneficial to the enrichment of BTB-WN.

Schlüsselwörter

  • MWEs
  • Wordnet
  • Wikipedia
  • Semantic Mapping
Uneingeschränkter Zugang

Sentiment Analysis of Tweets on Coronavirus Disease 2019 (COVID-19) Pandemic from Metro Manila, Philippines

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 141 - 155

Zusammenfassung

Abstract

From the outbreak of a novel COronaVIrus Disease (COVID-19) in Wuhan to the first COVID-19 case in the Philippines, Filipinos have been enthusiastically engaging on Twitter to convey their sentiments. As such, this paper aims to identify the public opinion of Filipino twitter users concerning COVID-19 in three different timelines. Toward this goal, a total of 65,396 tweets related to COVID-19 were sent to data analysis using R Statistical Software. Results show that “mask”, “health”, “lockdown”, “outbreak”, “test”, “kit”, “university”, “alcohol”, and “suspension” were some of the most frequently occurring words in the tweets. The study further investigates Filipinos’ emotions regarding COVID-19 by calculating text polarity of the dataset. To date, this is the first paper to perform sentiment analysis on tweets pertaining to COVID-19 not only in the Filipino context but worldwide as well.

Schlüsselwörter

  • Sentiment analysis
  • coronavirus disease
  • Philippines
  • Twitter
  • opinion mining
  • COVID-19
  • NCOV
  • virus
  • tweets
  • Data Mining
Uneingeschränkter Zugang

Predictive Analysis of Dengue Outbreak Based on an Improved Salp Swarm Algorithm

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 156 - 169

Zusammenfassung

Abstract

The purpose of this study is to enhance the exploration capability of conventional Salp Swarm Algorithm (SSA) with the inducing of Levy Flight. With such modification, it will assist the SSA from trapping in local optimum. The proposed approach, which is later known as an improved SSA (iSSA) is employed in monthly dengue outbreak prediction. For that matter, monthly dataset of rainfall, humidity, temperature and number of dengue cases were employed, which render prediction information. The efficiency of the proposed algorithm is evaluated using Root Mean Square Error (RMSE), and compared against the conventional SSA and Ant Colony Optimization (ACO). The obtained results suggested that the iSSA was not only able to produce lower RMSE, but also capable to converge faster at lower rate as well.

Schlüsselwörter

  • Dengue outbreak prediction
  • meta-heuristic
  • optimization
  • predictive analysis
  • Salp Swarm Algorithm
  • swarm intelligence
Uneingeschränkter Zugang

Why Perturbations?

Online veröffentlicht: 10 Dec 2020
Seitenbereich: 170 - 175

Zusammenfassung

Abstract

Review on the book M. M. Konstantinov, P. H. Petkov. Perturbation Methods in Matrix Analysis and Control. NOVA Science Publishers, Inc., New York, 2020. ISBN 978-1-53617-470-0. https://novapublishers.com/shop/perturbation-methods-in-matrix-analysis-and-control/

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