This paper is about the construction of various specific machine learning paradigms using a primitive-based generic machine learning model. The generic model identifies five functional components involved in a machine learning process, including an input, a transformation, a control, an output, and a knowledge base. It also identifies a set of basic machine learning mechanisms for each componen...

statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. this paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. the thermal conductivity of nanofluids increases with the volume fraction and temperature. machine learni...

background the presence of an infected family member significantly increases the risk of hbv transmission, but many socio-demographic and viral characteristics of family members affect the transmission rate. objectives in this study, we have used data mining techniques to investigate the impact of different variables in intrafamilial transmission of hbv infection. patients and methods demograph...

Modern machine learning and autonomous experimentation schemes in materials science rely on accurate analysis of the data ingested by these models. Unfortunately, underlying can be difficult, even for domain experts, complicating training models intended to drive experiments. This is especially true when goal identify presence weak signatures diffraction or spectroscopic datasets. In this work,...

Recent improvements in web standards and technologies enable the attackers to hide and obfuscate infectious codes with new methods and thus escaping the security filters. In this paper, we study the application of machine learning techniques in detecting malicious web pages. In order to detect malicious web pages, we propose and analyze a novel set of features including HTML, JavaScript (jQuery...

Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...

background: today, despite the many advances in early detection of diseases, cancer patients have a poor prognosis and the survival rates in them are low. recently, microarray technologies have been used for gathering thousands data about the gene expression level of cancer cells. these types of data are the main indicators in survival prediction of cancer. this study highlights the improvement...

Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for altera...