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The identification and prognosis of the potential for developing Cardiovascular Diseases (CVD) in healthy individuals is a vital aspect of disease management. Accessing the comprehensive health data on CVD cur...
The primary aim of this research paper is to introduce and demonstrate the application of the sine–cosine method and the convolution method for simulating data by utilizing the neutrosophic normal distribution.
Research on language teaching quality has certainly stood out enough to be noticed as the momentum higher school teaching change proceeds to extend and develop. The way to further developing language teaching ...
Hypernym discovery is challenging because it aims to find suitable instances for a given hyponym from a predefined hypernym vocabulary. Existing hypernym discovery methods used supervised learning with word em...
Although Parkinson’s disease (PD) has a heterogeneous disease course, it remains challenging to establish subtypes. We described and clustered the natural course of Parkinson’s disease (PD) with respect to fun...
The diagnosis and categorization of cardiac disease using the low-cost tool electrocardiogram (ECG) becomes an intriguing study topic when contemplating intelligent healthcare applications. An ECG-based cardia...
Fin-Tech is the merging of finance and technology, to be considered a key term for technology-based financial operations and money transactions as far as Fin-Tech is concerned. In the massive field of business...
Large unbalanced datasets pose challenges for machine learning models, as redundant and irrelevant features can hinder their effectiveness. Furthermore, the performance of intrusion detection systems (IDS) can...
Real-time object tracking and occlusion handling are critical research areas in computer vision and machine learning. Developing an efficient and accurate object-tracking method that can operate in real-time w...
The decision tree is a widely used decision support model, which can quickly mine effective decision rules based on the dataset. The decision tree induction algorithm for continuous-valued attributes, based on...
Screening for hyperthyroidism using gold-standard diagnostic criteria in the general population is not cost-effective, leading to a relatively high rate of undiagnosed and untreated patients. This study aimed ...
Nowadays, big data is an emerging area of computer science. Data are generated through different sources such as social media, e-commerce, blogs, banking, healthcare, transactions, apps, websites, opinion plat...
Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable biomarkers to predict pr...
The existing Fisher’s exact test has been widely applied for investigating whether the difference between the observed frequencies is significant or not. The existing Fisher’s exact test can be applied only wh...
Precision farming (PF) plays a crucial role in the field of agriculture to solve the challenges of food shortages in society. Heterogeneity, multicollinearity, and outliers are problems in PF because they can ...
Hepatocellular carcinoma (HCC) represents a formidable malignancy with a high lethality. Nonetheless, the development of vaccine and the establishment of prognostic models for precise and personalized treatmen...
Internet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of servi...
Answering questions related to the legal domain is a complex task, primarily due to the intricate nature and diverse range of legal document systems. Providing an accurate answer to a legal query typically nec...
The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals...
Disinformation campaigns on online social networks (OSN) in recent years, have underscored democracies’ vulnerability to such operations and the importance of identifying such operations and dissecting their m...
The study proposes a novel model for DNA sequence classification that combines machine learning methods and a pattern-matching algorithm. This model aims to effectively categorize DNA sequences based on their ...
Mobility data of a moving object, called trajectory data, are continuously generated by vessel navigation systems, wearable devices, and drones, to name a few. Trajectory data consist of samples that include t...
The behavior of a Vehicle Ad hoc Network (VANETs) is extremely unpredictable due to the high mobility and random network topology inherent to the nature of VANETs. Several problems, including frequent connecti...
Keratitis is a major cause of corneal blindness worldwide. Early identification and timely treatment of keratitis can deter the disease progression, reaching a better prognosis. The diagnosis of keratitis ofte...
The k-means, one of the most widely used clustering algorithm, is not only faster in computation but also produces comparatively better clusters. However, it has two major downsides, first it is sensitive to i...
Users on social networks such as Twitter interact with each other without much knowledge of the real-identity behind the accounts they interact with. This anonymity has created a perfect environment for bot ac...
The yearly increase in incidents of credit card fraud can be attributed to the rapid growth of e-commerce. To address this issue, effective fraud detection methods are essential. Our research focuses on the Cr...
Existing research in differential privacy, whose applications have exploded across functional areas in the last few years, describes an intrinsic trade-off between the privacy of a dataset and its utility for ...
Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience ...
The generation of synthetic data can be used for anonymization, regularization, oversampling, semi-supervised learning, self-supervised learning, and several other tasks. Such broad potential motivated the dev...
With the development of computer vision technology, the demand for deploying vision inspection tasks on edge mobile devices is becoming increasingly widespread. To meet the requirements of application scenario...
Rotary machines are constructed and operated in diverse industrial environments and operate according to various specifications and characteristics. When rotary machinery constructed under dynamic real world e...
In this paper a program and methodology for bibliometric mining of research trends and directions is presented. The method is applied to the research area Big Data for the time period 2012 to 2022, using the S...
Optical coherence tomography angiography (OCTA) has been a frequently used diagnostic method in neovascular age-related macular degeneration (nAMD) because it is non-invasive and provides a comprehensive view ...
Because of the rapid growth of mobile technology, social media has become an essential platform for people to express their views and opinions. Understanding public opinion can help businesses and political in...
Hate Speech encompasses different forms of trolling, bullying, harassment, and threats directed against specific individuals or groups. This phenomena is mainly expressed on Social Networks. For sports players...
Music Genre Classification (MGC) is a crucial undertaking that categorizes Music Genre (MG) based on auditory information. MGC is commonly employed in the retrieval of music information. The three main stages ...
General speech recognition models require large capacity and strong computing power. Based on small capacity and low computing power to realize speech analysis and semantic recognition is a research area with ...
Fraud datasets often times lack consistent and accurate labels, and are characterized by having high class imbalance where the number of fraudulent examples are far fewer than those of normal ones. Machine lea...
Human Skin cancer is commonly detected visually through clinical screening followed by a dermoscopic examination. However, automated skin lesion classification remains challenging due to the visual similaritie...
The rapid development of healthcare big data has brought certain convenience to medical research and health management, but privacy protection of healthcare big data is an issue that must be considered in the ...
In the most popular distributed stream processing frameworks (DSPFs), programs are modeled as a directed acyclic graph. Using this model, a DSPF can benefit from the parallelism capabilities of distributed clu...
Intrusion Detection is essential to identify malicious incidents and continuously alert many users of the Internet of Things (IoT). The constant monitoring of events generated from many devices connected to th...
Recently, assistive explanations for difficulties in the health check area have been made viable thanks in considerable portion to technologies like deep learning and machine learning. Using auditory analysis ...
Recent research has focused on exploring systems that incorporate anomaly detection models to automate the addition of users in user recognition systems. Anomaly detection, a method used to distinguish between...
With the emergence of Property Technology, online listing data have drawn increasing interest in the field of real estate–related big data research. Scraped from the online platforms for property search and ma...
In this article, we introduce a novel type of spatio-temporal sequential patterns called Constricted Spatio-Temporal Sequential (CSTS) patterns and thoroughly analyze their properties. We demonstrate that the ...
Nowadays, the online environment is extra information-rich and allows companies to offer and receive more and more options and opportunities in multiple areas. Thus, decision-makers have abundantly available a...
Continuously increasing data volumes from multiple sources, such as simulation and experimental measurements, demand efficient algorithms for an analysis within a realistic timeframe. Deep learning models have...
Processing large-scale graphs is challenging due to the nature of the computation that causes irregular memory access patterns. Managing such irregular accesses may cause significant performance degradation on...
2022 Citation Impact
8.1 - 2-year Impact Factor
5.095 - SNIP (Source Normalized Impact per Paper)
2.714 - SJR (SCImago Journal Rank)
2022 Speed
54 days submission to first editorial decision for all manuscripts (Median)
181 days submission to accept (Median)
2022 Usage
2,250,289 downloads
1,798 Altmetric mentions
