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Although many problems in computer vision and natural language processing have made breakthrough progress with neural networks, adversarial attack is a serious potential problem in many neural network- based applications. Attackers can mislead classifiers with slightly perturbed examples, which are called...

The notions of interior BCK/BCI-algebras, positive implicative interior BCK-algebras, (weak) interior ideals, positive implicative interior ideals, a positive implicative weak interior ideal of type 1, type 2, and type 3 are introduced, and related properties are investigated. A mapping is provided to...

Complex q-rung orthopair fuzzy set (CQROFS) contains the grade of supporting and the grade of supporting against in the form of polar coordinates belonging to unit disc in a complex plane and is a proficient technique to address awkward information, although the normal fuzzy number (NFN) examines normal...

A Software Product Line (SPL) is a collection of software for configuring software products in which sets of features are configured by different teams of product developers. This process often leads to inconsistencies (or dissatisfaction of constraints) in the resulting product configurations, whose...

Data augmentation is an important technique to improve the performance of deep learning models in many vision tasks such as object detection. Recently, some works proposed the copy-paste method, which augments training dataset by copying foreground objects and pasting them on background images. By designing...

A family of fuzzy mappings is called higher-order strongly preinvex fuzzy mappings (HOS-preinvex fuzzy mappings), which take the place of generalization of the notion of nonconvexity is introduced through the “fuzzy-max” order among fuzzy numbers. This family properly includes the family of preinvex...

Particle swarm optimization (PSO) tends to be premature convergence due to easily trapping into local suboptimal areas. In order to overcome the PSO's defects, the reasons causing the defects are analyzed and summarized as population diversity deficiency, insufficient information sharing, unbalance...

Data quality is the prerequisite of big data research and the basis of all data analysis, mining, and decision support. Therefore, a comprehensive fuzzy evaluation method for big data quality evaluation is proposed. Through the analysis of big data quality characteristics, a big data quality evaluation...

In semantic segmentation, category-hidden attack is a malicious adversarial attack which manipulates a specific category without affecting the recognition of other objects. A popular method is the nearest-neighbor algorithm, which modifies the segmentation map by replacing a target category with other...

It is well known that the concept of convexity establishes strong relationship with integral inequality for single-valued and interval-valued function. The single-valued function and interval-valued function both are special cases of fuzzy interval-valued function. The aim of this paper is to introduce...

In present decade, many Educational Institutions use classification techniques and Data mining concepts for evaluating student records. Student Evaluation and classification is very much important for improving the result percentage. Hence, Educational Data Mining based models for analyzing the academic...

Recently, we have introduced six types of composition of ternary fuzzy relations. These compositions are close in spirit to the composition of binary fuzzy relations. Based on these types of composition, we have introduced several types of transitivity of a ternary fuzzy relation and investigated their...

Finding cliques and clique covers in graphs are one of the most needful tasks. In this paper, interval-valued fuzzy cliques (IVFQs) and interval-valued fuzzy clique covers (IVFQCs) of an interval-valued fuzzy graph (IVFG) are introduced by introducing the fuzziness because, the crisp graphs has some...

An accurate prediction of future stock market trends is a bit challenging as it requires a profound understanding of stock technical indicators, including market-dominant factors and inherent process mechanism. However, the significance of better trading decisions for a successful trader inspires researchers...

Robotic grasp detection is a fundamental problem in robotic manipulation. The conventional grasp methods, using vision information only, can cause potential damage in force-sensitive tasks. In this paper, we propose a tactile–visual based method using a reproducible sensor to realize a fine-grained and...

The daily 10.7-cm Solar Radio Flux (F10.7) data is a time series with highly volatile. The accurate prediction of F10.7 has a great significance in the fields of aerospace and meteorology. At present, the prediction of F10.7 is mainly carried out by linear models, nonlinear models, or a combination of...

High-throughput experimental techniques such as genome-wide association studies have been instrumental in the identification of disease-associated genes. These methods often produce large lists of disease candidate genes which are time-consuming and expensive to experimentally validate. Computational...

Mining contrast subspace has emerged to find subspaces where a particular queried object is most similar to the target class against the non-target class in a two-class data set. It is important to discover those subspaces, which are known as contrast subspaces, in many real-life applications. Tree-Based...

Traffic congestion in urban areas has become a critical problem that municipal governments cannot overlook. Meanwhile, mixed traffic systems containing both autonomous and human-driven electric vehicles ramp up the challenge for traffic management in urban areas. Although numerous researchers have proposed...

The q-rung orthopair fuzzy set (qROFS) defined by Yager is a generalization of Atanassov intuitionistic fuzzy set (IFS) and Pythagorean fuzzy sets (PyFSs). In this paper, we define the knowledge measure for qROFS by using the cosine inverse function. The information precision and information content...

The computation of link prediction is one of the most important tasks on a social network. Several methods are available in the literature to predict links in networks and RSM index is one of them. The RSM index is applicable in the fuzzy environment and it does not incorporate the notion of falsity...

Many researchers have used fuzzy set theory and fuzzy logic in a variety of applications related to computer science and engineering, given the capability of fuzzy inference systems to deal with uncertainty, represent vague concepts, and connect human language to numerical data. In this work we propose...

Garment pattern design is an extremely significant factor for the success of fashion company in mass customization and industry 4.0. In this paper, we proposed a new approach for constructing a garment pattern design knowledge base (GPDKB) using sensory analysis, ontology and support vector regression...

In practical applications, some existing multi-attribute decision-making methods based on the L∗ fuzzy set theory suffer from a lot of shortcomings, namely, incorrect choice preference orders of alternatives are obtained in some cases. In this paper, we construct a new aggregation operator based on uninorms...

Diagnosing incipient faults of rotating machines is very important for reducing economic losses and avoiding accidents caused by faults. However, diagnoses of locations and sizes of incipient faults are very difficult in a noisy background. In this paper, we propose a fault diagnosis method that combines...

The number of function evaluations in many industrial applications of simulation-based optimization problems is strictly limited. Therefore, only little analytical information on objective and constraint functions is available. This paper presents an adaptive algorithm called the Surrogate-Based Constrained...

As a modification of the q-rung orthopair fuzzy sets (QROFSs), complex QROFSs (CQROFSs) can describe the inaccurate information by complex-valued truth grades with an additional term, named as phase term. Cosine similarity measures (CSMs) and distance measures (DMs) are important tools to verify the...

Several new resampling methods for generating bootstrap samples of fuzzy numbers are proposed. To avoid undesired repetitions in the secondary samples we do not draw randomly directly observations from the primary samples but construct them allowing for some modifications in their membership functions,...

Water-energy-food (W-E-F) nexus is an essential element for human survival, as well as the basis for the sustainable development of regional economy and ecological environment. Water resource is an important input element of energy production and food production, which makes the W-E-F nexus become closer...

Blockchain is a decentralized distributed ledger technology. The public chain represented by Bitcoin and Ethereum only realizes the limited anonymity of user identity, and the transaction amount is open to the whole network, resulting in user privacy leakage. Based on the existing anonymous technology,...

In this paper we introduce the concept of multiple bipolar fuzzy measures as a generalization of a bipolar fuzzy measure. We also propose a new definition of a group, which is based on the multidimensional bipolar fuzzy relations of its elements. Taking into account this information, we provide a novel...

Algorithms based on convolutional neural networks (CNNs) have been great attention in image processing due to their ability to find patterns and recognize objects in a wide range of scientific and industrial applications. Finding the best network and optimizing its hyperparameters for a specific application...

In this paper, we study the value function with regret minimization algorithm for solving the Nash equilibrium of multi-agent stochastic game (MASG). To begin with, the idea of regret minimization is introduced to the value function, and the value function with regret minimization algorithm is designed....

Music has a great role and importance in human life since it has the ability to trigger or convey feelings. As recognizing music emotions is the subject of many studies conducted in many disciplines like science, psychology, musicology and art, it has attracted the attention of researchers as an up-to-date...

Information structures (i-structures) in an ordered information system (OIS) are mathematical structures of the information granules (i-granules) granulated from the data set of this OIS. This article investigates i-structures in an OIS with granular computing (GrC) view, i.e., i-structures in an OIS...

In the traditional portfolio selection problem, asset returns are modeled as fuzzy variables with fuzzy return. However, this approach is limited in its ability to capture uncertainty accurately and in analytical model solving. Here, we aim to develop a new fuzzy chance-constrained portfolio model with...

This article proposes a character-level neural language model (NLM) that is based on quantum theory. The input of the model is the character-level coding represented by the quantum semantic space model. Our model integrates a convolutional neural network (CNN) that is based on network-in-network (NIN)....

Class imbalance is a common issue in medical diagnosis. Although standard radial basis function neural network (RBF-NN) has achieved remarkably high performance on balanced data, its ability to classify imbalanced data is still limited. So far as we know, cost-sensitive learning is an advanced imbalanced...

COVID-19 is an infectious disease caused by virus SARS-CoV-2 virus. Early classification of COVID-19 is essential for disease cure and control. Transcription-polymerase chain reaction (RT-PCR) is used widely for the detection of COVID-19. However, its high cost, time-consuming and low sensitivity will...

To date, the subgroup discovery (SD) task has been considered in problems where a target variable is unequivocally described by a set of features, also known as instance. Nowadays, however, with the increasing interest in data storage, new data structures are being provided such as the multiple instance...

Accurate identification of microRNA regulatory modules can give insights to understand microRNA synergistical regulatory mechanism. However, the identification accuracy suffers from incomplete biological data. In this paper, we proposed a learning-based framework called MicroRNA regulatory module dentification...

A dynamic Grey Wolf Optimizer (GWO) is proposed, noted as DGWO2, and a novel dynamic improved GWO algorithm is obtained after transferring the mutation operator and the eliminating–reconstructing mechanism to the DGWO2, noted as DMR-GWO2. A Type-2 fuzzy predictive compensation PID trajectory tracking...

In recent years, more and more attention has been paid to single image super-resolution reconstruction (SISR) by using deep learning networks. These networks have achieved good reconstruction results, but how to make better use of the feature information in the image, how to improve the network convergence...

In the big data background, the uncertainty of data is increasingly apparent. Multi-polar fuzzy feature of data has been more popularly used by the research community for the purpose of the classification of weighing cheating in dynamic truck scale characteristic and the clustering problem of multi-polar...

Intelligent traffic system (ITS) is one of the effective ways to solve the problem of traffic congestion. As an important part of ITS, traffic index prediction is the key of traffic guidance and traffic control. In this paper, we propose a method integrating pattern feature to sequence model for traffic...

This study has aimed to examine the empirically relationship between strategic management of organizational knowledge and awareness about artificial intelligence (AI) through mediating effect of learning climate in service sector of Saudi Arabia. For better understanding, a structural questionnaire was...

Type 2 diabetes mellitus (T2DM) has been identified as one of the most challenging chronic diseases to manage. In recent years, the incidence of T2DM has increased, which has seriously endangered people’s health and life quality. Glycosylated hemoglobin (HbA1c) is the gold standard clinical indicator...

As an important part of human cultural heritage, many ancient paintings have suffered from various deteriorations that have led to texture blurring, color fading, etc. Single image super-resolution (SISR) which aims to recover a high-resolution (HR) version from a low-resolution (LR) input is actively...

Teacher engagement is a newly-emerged concept in the field of Indonesian teacher education. To support this concept, we designed an artificial neural network (ANN) using backpropagation, stochastic learning, and steepest gradient descent algorithms to determine teacher engagement based on the Indonesian...

Pacemaker logs are used to predict the progression of paroxysmal cardiac arrhythmia to permanent atrial fibrillation by means of different deep learning algorithms. Recurrent Neural Networks are trained on data produced by a generative model. The activations of the different nets are displayed in a graphical...