-
Hybrid Vessel Extraction Method Based on Tight-Frame and EM Algorithms by Using 2D Dual Tree Complex Wavelet Informatica (IF 3.312) Pub Date : 2021-02-11 Farid Abdollahi; Mehrdad Lakestani; Mohsen Razzaghi
The vessel extraction is very important for the vascular disease diagnosis and grading of the stenoses and aneurysms in vessels. This aids in brain surgery and making angioplasty. The presence of noise in the MRA image, etc., turns the vessel extraction into a difficult problem. In this paper, we derive a vessel extraction algorithm based on TFA and EMS algorithms. We prove the convergence of the proposed
-
Distributed Trust, a Blockchain Election Scheme Informatica (IF 3.312) Pub Date : 2021-02-08 Antonio M. Larriba; Aleix Cerdà i Cucó; José M. Sempere; Damián López
Voting systems are as useful as people are willing to use them. Although many electronic election schemes have been proposed through the years, and some real case scenarios have been tested, people still do not trust electronic voting. Voting is not only about technological challenges but also about credibility, therefore, we propose a voting system focused on trust. We introduce political parties
-
A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development Informatica (IF 3.312) Pub Date : 2021-01-29 Diana Kalibatienė; Jolanta Miliauskaitė
The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in fuzzy inference systems (FIS) development. However, researchers highlight different challenges and issues of this FIS development because of its complexity. This paper evaluates the current state of the art of FIS development complexity issues in Computer Science, Software Engineering
-
PFA-GAN: Pose Face Augmentation Based on Generative Adversarial Network Informatica (IF 3.312) Pub Date : 2021-01-29 Bassel Zeno; Ilya Kalinovskiy; Yuri Matveev
In this work, we propose a novel framework based on Generative Adversarial Networks for pose face augmentation (PFA-GAN). It enables a controlled pose synthesis of a new face image from a source face given a driving one while preserving the identity of the source face. We introduce a method for training the framework in a fully self-supervised mode using a large-scale dataset of unconstrained face
-
Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images Informatica (IF 3.312) Pub Date : 2021-01-12 Elzbieta Budginaitė; Mindaugas Morkūnas; Arvydas Laurinavičius; Povilas Treigys
Anti-cancer immunotherapy dramatically changes the clinical management of many types of tumours towards less harmful and more personalized treatment plans than conventional chemotherapy or radiation. Precise analysis of the spatial distribution of immune cells in the tumourous tissue is necessary to select patients that would best respond to the treatment. Here, we introduce a deep learning-based workflow
-
Controlling Supervised Industry 4.0 Processes through Logic Rules and Tensor Deformation Functions Informatica (IF 3.312) Pub Date : 2021-01-12 Borja Bordel; Ramón Alcarria; Tomás Robles
Industry 4.0 solutions are composed of autonomous engineered systems where heterogeneous agents act in a choreographed manner to create complex workflows. Agents work at low-level in a flexible and independent manner, and their actions and behaviour may be sparsely manipulated. Besides, agents such as humans tend to show a very dynamic behaviour and processes may be executed in a very anarchic, but
-
Risk Prioritization in Failure Mode and Effects Analysis with Extended SWARA and MOORA Methods Based on Z-Numbers Theory Informatica (IF 3.312) Pub Date : 2020-12-18 Saeid Jafarzadeh Ghoushchi; Kazhal Gharibi; Elnaz Osgooei; Mohd Nizam Ab Rahman; Mohammad Khazaeili
This study introduces an approach in three phases to cover the disadvantages of the FMEA method including inability to assign different importance to risk factors and incomplete prioritization in uncertain environment. First, the values of Risk Priority Number (RPN) are set through the FMEA method. Then, the Step-wise Weight Assessment Ratio Analysis based on the Z-Number theory (Z-SWARA) method has
-
Nonconvex Total Generalized Variation Model for Image Inpainting Informatica (IF 3.312) Pub Date : 2020-12-08 Xinwu Liu
It is a challenging task to prevent the staircase effect and simultaneously preserve sharp edges in image inpainting. For this purpose, we present a novel nonconvex extension model that closely incorporates the advantages of total generalized variation and edge-enhancing nonconvex penalties. This improvement contributes to achieve the more natural restoration that exhibits smooth transitions without
-
Spherical Fuzzy Linear Assignment Method for Multiple Criteria Group Decision-Making Problems Informatica (IF 3.312) Pub Date : 2020-12-02 Yaser Donyatalab; Seyed Amin Seyfi-Shishavan; Elmira Farrokhizadeh; Fatma Kutlu Gündoğdu; Cengiz Kahraman
Spherical fuzzy sets theory is useful and advantageous for handling uncertainty and imprecision in multiple attribute decision-making problems by considering membership, non-membership, and indeterminacy degrees. In this paper, by extending the classical linear assignment method, we propose a novel method called the spherical fuzzy linear assignment method (SF-LAM) to solve multiple criteria group
-
-
Robust Dynamic Programming in N Players Uncertain Differential Games Informatica (IF 3.312) Pub Date : 2020-11-23 Manuel Jiménez-Lizárraga; Sara V. Rodríguez-Sánchez; Naín de la Cruz; César Emilio Villarreal
In this paper we consider a non-cooperative N players differential game affected by deterministic uncertainties. Sufficient conditions for the existence of a robust feedback Nash equilibrium are presented in a set of min-max forms of Hamilton–Jacobi–Bellman equations. Such conditions are then used to find the robust Nash controls for a linear affine quadratic game affected by a square integrable uncertainty
-
The Analysis of the Characteristics and Evolution of the Collaboration Network in BD Informatica (IF 3.312) Pub Date : 2020-11-20 Dejian Yu; Yitong Chen
Blockchain is a decentralized database, which can protect the safety of trade and avoid double payment. Due to the widespread attention of researchers, the studies of this field have increased sharply in recent years. It is meaningful to reveal the development level and trends based on this literature. This paper adopts bibliometric methods to study the collaboration characteristics from the levels
-
Series with Binomial-Like Coefficients for Evaluation and 3D Visualization of Zeta Functions Informatica (IF 3.312) Pub Date : 2020-11-09 Igoris Belovas; Martynas Sabaliauskas
In this paper, we continue the study of efficient algorithms for the computation of zeta functions on the complex plane, extending works of Coffey, Šleževičienė and Vepštas. We prove a central limit theorem for the coefficients of the series with binomial-like coefficients used for evaluation of the Riemann zeta function and establish the rate of convergence to the limiting distribution. An asymptotic
-
A Parallel Algorithm for Solving a Two-Stage Fixed-Charge Transportation Problem Informatica (IF 3.312) Pub Date : 2020-10-15 Ovidiu Cosma; Petrică C. Pop; Daniela Dănciulescu
This paper deals with the two-stage transportation problem with fixed charges, denoted by TSTPFC. We propose a fast solving method, designed for parallel environments, that allows solving real-world applications efficiently. The proposed constructive heuristic algorithm is iterative and its primary feature is that the solution search domain is reduced at each iteration. Our achieved computational results
-
An Extended Intuitionistic Fuzzy Multi-Attributive Border Approximation Area Comparison Approach for Smartphone Selection Using Discrimination Measures Informatica (IF 3.312) Pub Date : 2020-10-15 Arunodaya Raj Mishra; Abhishek Kumar Garg; Honey Purwar; Pushpendra Rana; Huchang Liao; Abbas Mardani
The objective of the paper is to introduce a novel approach using the multi-attribute border approximation area comparison (MABAC) approach under intuitionistic fuzzy sets (IFSs) to solve the smartphone selection problem with incomplete weights or completely unknown weights. A novel discrimination measure of IFSs is proposed to calculate criteria weights. In view of the fact that the ambiguity is an
-
Long Short-Term Memory Networks for Traffic Flow Forecasting: Exploring Input Variables, Time Frames and Multi-Step Approaches Informatica (IF 3.312) Pub Date : 2020-10-06 Bruno Fernandes; Fabio Silva; Hector Alaiz-Moreton; Paulo Novais; Jose Neves; Cesar Analide
Traffic flow forecasting is an acknowledged time series problem whose solutions have been essentially grounded on statistical-based models. Recent times came, however, with promising results regarding the use of Recurrent Neural Networks (RNNs), such as Long Short-Term Memory networks (LSTMs), to accurately address time series problems. Literature is, however, evasive in regard to several aspects of
-
Linguistic Summaries in Evaluating Elementary Conditions, Summarizing Data and Managing Nested Queries Informatica (IF 3.312) Pub Date : 2020-09-30 Pavol Sojka; Miroslav Hudec; Miloš Švaňa
Data users are generally interested in two types of aggregated information: summarization of the selected attribute(s) for all considered entities, and retrieval and evaluation of entities by the requirements posed on the relevant attributes. Less statistically literate users (e.g. domain experts) and the business intelligence strategic dashboards can benefit from the linguistic summarization, i.e
-
Business Process Management Systems: Evolution and Development Trends Informatica (IF 3.312) Pub Date : 2020-09-24 Marek Szelągowski; Audrone Lupeikiene
One of the results of the evolution of business process management (BPM) is the development of information technology (IT), methodologies and software tools to manage all types of processes – from traditional, structured processes to unstructured processes, for which it is not possible to define a detailed flow as a sequence of tasks to be performed before implementation. The purpose of the article
-
The Importance of Speckle Tracking Echocardiography Evaluating of Nonobstructive Coronary Artery Stenosis and Its Correlation with Microvascular Angina Informatica (IF 3.312) Pub Date : 2020-09-24 Kristina Morkunaite; Tautvydas Platukis; Egle Rumbinaite; Ramunas Unikas; Darijus Skaudickas; Marcel Abras; Vincentas Veikutis; Narseta Mickuviene
This study aims to evaluate patients with limited state of changes in coronary arteries detected by coronary angiography, the dynamics of these changes over the two years, identify the relevant diagnostic criteria, and assess the efficacy of applied treatment by using speckle tracking echocardiography. Peak radial and circumferential strain and SR (systolic, early, and late diastolic strains) were
-
Efficient Image Encryption Scheme Based on 4-Dimensional Chaotic Maps Informatica (IF 3.312) Pub Date : 2020-09-24 Ali Kanso; Mohammad Ghebleh; Abdullah Alazemi
This paper proposes a new family of 4-dimensional chaotic cat maps. This family is then used in the design of a novel block-based image encryption scheme. This scheme is composed of two independent phases, a robust light shuffling phase and a masking phase which operate on image-blocks. It utilizes measures of central tendency to mix blocks of the image at hand to enhance security against a number
-
Group Key Establishment in a Quantum-Future Scenario Informatica (IF 3.312) Pub Date : 2020-09-15 María Isabel González Vasco; Ángel L. Pérez del Pozo; Rainer Steinwandt
In cryptography, key establishment protocols are often the starting point paving the way towards secure execution of different tasks. Namely, the parties seeking to achieve some cryptographic task, often start by establishing a common high-entropy secret that will eventually be used to secure their communication. In this paper, we put forward a security model for group key establishment ($\mathsf{GAKE}$)
-
Perceptual Autoencoder for Compressive Sensing Image Reconstruction Informatica (IF 3.312) Pub Date : 2020-06-17 Ivan Ralašić; Damir Seršić; Siniša Šegvić
This paper presents a non-iterative deep learning approach to compressive sensing (CS) image reconstruction using a convolutional autoencoder and a residual learning network. An efficient measurement design is proposed in order to enable training of the compressive sensing models on normalized and mean-centred measurements, along with a practical network initialization method based on principal component
-
A Lossless Linear Algebraic Secret Image Sharing Scheme Informatica (IF 3.312) Pub Date : 2020-06-17 Ali Kanso; Mohammad Ghebleh; Abdullah Alazemi
A $(k,n)$-threshold secret image sharing scheme is any method of distributing a secret image amongst n participants in such a way that any k participants are able to use their shares collectively to reconstruct the secret image, while fewer than k shares do not reveal any information about the secret image. In this work, we propose a lossless linear algebraic $(k,n)$-threshold secret image sharing
-
A Reversible Data Hiding Based on Histogram Shifting of Prediction Errors for Two-Tier Medical Images Informatica (IF 3.312) Pub Date : 2020-06-22 Li-Chin Huang; Shu-Fen Chiou; Min-Shiang Hwang
Clinics and hospitals have already adopted more technological resources to provide a faster and more precise diagnostic for patients, health care providers, and institutes of medicine. Security issues get more and more important in medical services via communication resources such as Wireless-Fidelity (Wi-Fi), third generation of mobile telecommunications technology (3G), and other mobile devices to
-
An Entropy-Based Method for Probabilistic Linguistic Group Decision Making and its Application of Selecting Car Sharing Platforms Informatica (IF 3.312) Pub Date : 2020-07-15 Gai-li Xu; Shu-Ping Wan; Jiu-Ying Dong
As the tourism and mobile internet develop, car sharing is becoming more and more popular. How to select an appropriate car sharing platform is an important issue to tourists. The car sharing platform selection can be regarded as a kind of multi-attribute group decision making (MAGDM) problems. The probabilistic linguistic term set (PLTS) is a powerful tool to express tourists’ evaluations in the car
-
Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology Informatica (IF 3.312) Pub Date : 2020-07-29 Savíns Puertas-Martín; Juana L. Redondo; Horacio Pérez-Sánchez; Pilar M. Ortigosa
Ligand Based Virtual Screening methods are widely used in drug discovery as filters for subsequent in-vitro and in-vivo characterization. Since the databases processed are enormously large, this pre-selection process requires the use of fast and precise methodologies. In this work, the similarity between compounds is measured in terms of electrostatic potential. To do so, we propose a new and alternative
-
Extended TODIM Based on Cumulative Prospect Theory for Picture Fuzzy Multiple Attribute Group Decision Making Informatica (IF 3.312) Pub Date : 2020-06-08 Mengwei Zhao; Guiwu Wei; Cun Wei; Jiang Wu; Yanfeng Guo
Picture fuzzy sets (PFSs) utilize the positive, neutral, negative and refusal membership degrees to describe the behaviours of decision-makers in more detail. In this article, we expound the application of extended TODIM based on cumulative prospect theory under picture fuzzy multiple attribute group decision making (MAGDM). In addition, we adopt Information Entropy, which is used to ascertain the
-
MACONT: Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria Analysis Informatica (IF 3.312) Pub Date : 2020-06-08 Zhi Wen; Huchang Liao; Edmundas Kazimieras Zavadskas
Normalization and aggregation are two most important issues in multi-criteria analysis. Although various multi-criteria decision-making (MCDM) methods have been developed over the past several decades, few of them integrate multiple normalization techniques and mixed aggregation approaches at the same time to reduce the deviations of evaluation values and enhance the reliability of the final decision
-
A Group Decision Making Method with Interval-Valued Intuitionistic Fuzzy Preference Relations and Its Application in the Selection of Cloud Computing Vendors for SMEs Informatica (IF 3.312) Pub Date : 2020-06-08 Shaolin Zhang; Jie Tang; Fanyong Meng; Ruiping Yuan
To solve the problem of choosing the appropriate cloud computing vendors in small and medium-sized enterprises (SMEs), this paper boils it down to a group decision making (GDM) problem. To facilitate the judgment, this paper uses preference relation as the decision making technology. Considering the situation where uncertain positive and negative judgments exist simultaneously, interval-valued intuitionistic
-
Kriging Predictor for Facial Emotion Recognition Using Numerical Proximities of Human Emotions Informatica (IF 3.312) Pub Date : 2020-06-02 Rasa Karbauskaitė; Leonidas Sakalauskas; Gintautas Dzemyda
Emotion recognition from facial expressions has gained much interest over the last few decades. In the literature, the common approach, used for facial emotion recognition (FER), consists of these steps: image pre-processing, face detection, facial feature extraction, and facial expression classification (recognition). We have developed a method for FER that is absolutely different from this common
-
A Discrete Competitive Facility Location Model with Minimal Market Share Constraints and Equity-Based Ties Breaking Rule Informatica (IF 3.312) Pub Date : 2020-05-19 Pascual Fernández; Algirdas Lančinskas; Blas Pelegrín; Julius Žilinskas
We consider a geographical region with spatially separated customers, whose demand is currently served by some pre-existing facilities owned by different firms. An entering firm wants to compete for this market locating some new facilities. Trying to guarantee a future satisfactory captured demand for each new facility, the firm imposes a constraint over its possible locations (a finite set of candidates):
Contents have been reproduced by permission of the publishers.