One of the Internet of Things (IoT) security issues is the secure sharing and granular management of data access. This study recommends a feature-based encryption scheme with a hidden access structure for medical IoT data security. While establishing fine-grained access control of ciphertext...

This study proposes two types of bivariate Poisson extended exponential distributions: the basic bivariate Poisson extended exponential distribution and the Sarmanov-based bivariate Poisson extended exponential distribution. The two bivariate Poisson extended exponential distributions are then...

Online Portfolio Selection (OLPS) has attracted extensive interest in recent years. Accurate prediction of future prices and determining the optimal portfolio selection strategy based on the estimated return is a challenging topic in machine learning. We propose a novel adjusted learning...

This study proposes a novel entropy function for the intuitionistic fuzzy sets to improve the existing fuzzy entropy measure. We introduce an attitude-based entropy measure by methodically calculating the experts' attitude values through variance approach. We discuss several important properties...

A conflicting claims problem arises when a group of agents have claims over a resource that add up to more than it is available. Typical situations are the division of property among heirs, bankruptcy problems, tax distribution, or the global emissions budget. This paper introduces the R package...

Zero-shot classification refers to assigning a label to a text (sentence, paragraph, whole paper) without prior training. This is possible by teaching the system how to codify a question and find its answer in the text. In many domains, especially health sciences, systematic reviews are...

This study aims to design supply chain networks by considering strategic and operational decisions, increasing network efficiency, and reducing costs. Optimizing strategic decisions such as location of facilities, and operational decisions such as vehicle routing, greatly affect the network's...

Fraudsters are now more active in their attacks on credit card transactions than ever before. With the advancement in data science and machine learning, various algorithms have been developed to determine whether a transaction is fraudulent. We study the performance of three different machine...

An outlier is a datum that is far from other data points in which it occurs. It can have a considerable impact on the output. Therefore, removing or resolving it before the analysis is essential to prevent skewing. Outliers in a survey sampling can have a significant outcome on statistical...

The valuation of house prices is drawing noteworthy attention due to worldwide financial and real estate crises in the last decade. Therefore, there is an immediate need to design more effective predictive systems of house prices. Indeed, investors, creditors, and governments are all interested...