Assessing the impact of authors in scientific research is crucial for evaluating scholarly contributions. Various parameters exist in the literature to quantify researchers’ productivity, such as publication count, citation count, and the h index.

In the development of the social-economics of countries, time series is a data type stored commonly nowadays. For these data, forecasting has always received the attention of statisticians and managers because it brings to great advantages.

Light pollution is a problem that impacts many elements of human life and the environment, including astronomical observations. The authors of this work offer a unique method for detecting anomalies in night sky brightness data recorded using a …

The aim of this study is to enhance the extraction of informative features from complex data through the application of topological data analysis (TDA) using novel topological overlapping measures. Topological data analysis has emerged as a …

People’s lives are always threatened by various diseases. The role of health and medical services, in particular medicine, is undeniable in protecting their lives. Timely preparation and providing medicine for patients is vital since medicine …

A challenge faced while monitoring the COVID-19 pandemic in Brazil is the identification of patterns of incidence and mortality, which can help prioritize interventions to avoid excessive disease transmission and associated deaths. This study …

Knowledge graph-based visual question answering aims to utilize the information in the knowledge graph to assist in answering complex questions that are difficult to answer based on image features alone. However, using knowledge graphs increases …

The field of AI Ethics has recently gained considerable attention, yet much of the existing academic research lacks practical and objective contributions for the development of ethical AI systems. This systematic literature review aims to identify …

Frequent itemset mining (FIM) has firmly established itself as a pivotal and reliable tool in the realm of business analytics, enabling the systematic discovery of valuable patterns and association rules within extensive datasets. However, FIM has …

Machine learning enhances predictive ability in various research compared to conventional statistical approaches. However, the advantage of the regression model is that it can effortlessly interpret the effect of each predictor. Therefore …

The advent of technology has facilitated communication among individuals, structures, and transport, thereby revolutionizing contemporary living. In this regard, the Internet of Things has emerged as a transformative approach. Smart vehicles and …

Document clustering involves grouping together documents so that similar documents are grouped together in the same cluster and different documents in the different clusters. Clustering of documents is considered a fundamental problem in the field …

The Internet of Things is an emerging domain in the field of establishing the effective communications. Routing protocols are crucial for ensuring dependable data transmission in networks with limited resources. RPL is a standardized protocol used …

Fake news and misinformation spread in online social networks in a manner similar to contagious diseases. One possibility to thwart the contagion cascade is to selectively remove a small number of nodes from the network. Although most of the …

Discovering features that set elite players apart is of great significance for eSports coaches as it enables them to arrange a more effective training program focused on improving those features. Moreover, finding such features results in a better …

Feature selection is popular for obtaining small, interpretable, yet highly accurate prediction models. Conventional feature-selection methods typically yield one feature set only, which does not suffice in certain scenarios. For example, users …

Developing an effective modeling framework to minimize foreign exchange (FX) risk is of vital importance for hedgers and traders in FX markets. In this study, we compare the ability of long short-term memory (LSTM) models to that of random forest …

Traffic sensor data are prone to malfunctions caused by various factors such as manufacturing defects, harsh environmental conditions, improper installation, and maintenance. While fault data detection is a well-established practice in many …

Geo-referenced and temporal data are becoming more and more ubiquitous in a wide range of fields such as medicine and economics. Particularly in the realm of medical research, spatio-temporal data play a pivotal role in tracking and understanding …