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Triadic patent (TP) families and Patent Cooperation Treaty (PCT) applications are often used as datasets to measure innovation capability or R&D internationalization, but their concordance is unclear, which is...
The metaverse has become one of the most popular concepts of recent times. Companies and entrepreneurs are fiercely competing to invest and take part in this virtual world. Millions of people globally are anti...
Sleep disorders are significant health concerns affecting a large population. Related clinical studies face the deficiency in sleep data and challenges in data analysis, which requires enormous human expertise...
This research analyzes the area required for the conflict resolution between aircraft in two flows impacted by a convective weather cell (CWC). The CWC is introduced as a constrained area, forbidden to flight ...
Stroke has become a significant threat to global public health, the ideal solution to which is primary prevention. Identification and management of determinants of stroke among various variables in different d...
The super power of deep learning in image classification problems have become very popular and applicable in many areas like medical sciences. Some of the medical applications are real-time and may be implemen...
SRAM and DRAM memory technologies have been dominant in the implementations of memory subsystems. In recent years, and mainly driven by the huge memory demands of big data applications, NVRAM technology has em...
Person Re-identification (ReID) is the process of matching target individuals to their images within different images or videos captured from a variety of angles or cameras. This is a critical task for surveil...
This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best perfor...
The healthcare industry is different from other industries–patient data are sensitive, their storage needs to be handled with care and in compliance with regulative, while prediction accuracy needs to be high....
In this paper, we solve the well-known symbolic regression problem that has been intensively studied and has a wide range of applications. To solve it, we propose an efficient metaheuristic-based approach, cal...
Hepatocellular carcinoma (HCC) has a desmoplastic and hypoxic tumor microenvironment (TME), resulting in poor prognosis and treatment resistance. This study aimed to construct a novel prognostic classifier to ...
Influentials play a key role in enhancing information diffusion on social media. However, how personal influence varies across multiple domains is rarely addressed. This study introduces a concept called Domai...
Sensors and smart equipment are frequently used in biomechanical systems and applications in sports and rehabilitation to measure various physical quantities. Various sensors, measuring different parameters, c...
In this study, two machine-learning algorithms based on the artificial neural network (ANN) model are proposed to estimate the ultimate compressive strength of square concrete-filled steel tubular columns. The...
The proposed framework consists of three modules as an outlier detection method for indoor air quality data. We first use a long short-term memory autoencoder (LSTM-AE) based reconstruction error detector, whi...
Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of user...
The number of published scientific paper grows rapidly each year, totaling more than 2.9 million annually. New methodologies and systems have been developed to analyze scientific production and performance ind...
Women are prone to breast cancer, which is a major cause of death. One out of every eight women has a lifetime risk of developing this cancer. Early diagnosis of this disease is critical and enhances the succe...
Autonomous cars have achieved exceptional growth in the automotive industry in the last century in terms of reliability, safety and affordability. Due to significant advancements in computing, communication an...
Revisit intention is a key indicator of business performance, studied in many fields including hospitality. This work employs big data analytics to investigate revisit intention patterns from tourists’ electro...
Embedding knowledge graphs into low-dimensional spaces is a popular method for applying approaches, such as link prediction or node classification, to these databases. This embedding process is very costly in ...
Output thresholding is well-suited for addressing class imbalance, since the technique does not increase dataset size, run the risk of discarding important instances, or modify an existing learner. Through the...
Extensive prior work has provided methods for the optimization of routing based on weights assigned to travel duration, and/or travel cost, and/or the distance traveled. Routing can be in various modalities, s...
The panorama of data is ever evolving, and big data has emerged to become one of the most hyped terms in the industry. Today, users are the perpetual producers of data that if gleaned and crunched, have the po...
Multiple organ dysfunction syndrome (MODS) is one of the leading causes of death in critically ill patients. MODS is the result of a dysregulated inflammatory response that can be triggered by various causes. ...
This paper presents a transfer learning approach to the crop classification problem based on time series of images from the Sentinel-2 dataset labeled for two regions: Brittany (France) and Vojvodina (Serbia)....
Distributed computing continuum systems (DCCS) make use of a vast number of computing devices to process data generated by edge devices such as the Internet of Things and sensor nodes. Besides performing compu...
Precision agriculture in the realm of the Internet of Things is characterized by the collection of data from multiple sensors deployed on the farm. These data present a spatial, temporal, and semantic characte...
In the pre-big data era, many traditional databases supported spatial queries via spatial indexes. However, modern applications are seeing a rapid increase of the volume and ingestion rate of spatial data. Log...
Sentiment analysis is the most trending and ongoing research in the field of data mining. Nowadays, several social media platforms are developed, among that twitter is a significant tool for sharing and acquir...
Given a dataset V of points from some metric space, a popular robust formulation of the k-center clustering problem requires to select k points (centers) of V which minimize the maximum distance of any point of V
The success of the business directly contributes towards the growth of the nation. Hence it is important to evaluate and predict whether the business will be successful or not. In this study, we use the compan...
Traditional Food Knowledge (TFK) is needed to define the acculturation of culture, society, and health in the context of food. TFK is essential for a human’s cultural, economic, and health aspects. Variations ...
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data ...
Rumor posts have received substantial attention with the rapid development of online and social media platforms. The automatic detection of rumor from posts has emerged as a major concern for the general publi...
This article examines the engagement of domestic actors in public conversation surrounding free trade negotiations with a focus on the framing of these negotiations as economic, strategic or domestic issues. T...
Most semantic segmentation approaches of big data hyperspectral images use and require preprocessing steps in the form of patching to accurately classify diversified land cover in remotely sensed images. These...
Using the wrong metrics to gauge classification of highly imbalanced Big Data may hide important information in experimental results. However, we find that analysis of metrics for performance evaluation and wh...
Customer churn is a major issue for large enterprises. In particular, in the rental business sector, companies are looking for ways to retain their customers because they are their main source of revenue. The ...
Clustering a big dataset without knowing the number of clusters presents a big challenge to many existing clustering algorithms. In this paper, we propose a Random Sample Partition-based Centers Ensemble (RSPC...
Oral cancer may arise from oral leukoplakia and oral lichenoid mucositis (oral lichen planus and oral lichenoid lesions) subtypes of oral potentially malignant disorders. As not all patients will develop oral ...
The random forest algorithm could be enhanced and produce better results with a well-designed and organized feature selection phase. The dependency structure between the variables is considered to be the most ...
The automatic classification of marine species based on images is a challenging task for which multiple solutions have been increasingly provided in the past two decades. Oceans are complex ecosystems, difficu...
This study aims to improve the accuracy of forecasting the turnover intention of new college graduates by solving the imbalance data problem. For this purpose, data from the Korea Employment Information Servic...
Short text information has considerable commercial value and immeasurable social value. Natural language processing and short text sentiment analysis technology can organize and analyze short text information ...
We are living in an age where data is everywhere and grows up in a very speedy way. Thanks to sensors, mobile phones and social networks, we can gather a hug amount of information to understand human behavior ...
The detection of anomalous behavior in business process data is a crucial task for preventing failures that may jeopardize the performance of any organization. Supervised learning techniques are impracticable ...
The emerging topic of sequential recommender (SR) has attracted increasing attention in recent years, which focuses on understanding and learning the sequential dependencies of user behaviors hidden in the use...
2022 Citation Impact
8.1 - 2-year Impact Factor
5.095 - SNIP (Source Normalized Impact per Paper)
2.714 - SJR (SCImago Journal Rank)
2023 Speed
56 days submission to first editorial decision for all manuscripts (Median)
205 days submission to accept (Median)
2023 Usage
2,559,548 downloads
280 Altmetric mentions
