Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show MoreThe current research aims to provide a conceptual and applied frame on the subject of multi- level analysis in the research of business administration. The research tries to address some of the problems that befall the preparation of research and studies at the Arab level and local level, where the unity of theory and measurement and analysis, as well as clarify the various types of conceptual constructs and give researchers the ability to distinguish different models related to the level of analysis. On the other hand, this research provides an example of
... Show MoreToday, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.
In all process industries, the process variables like flow, pressure, level, concentration
and temperature are the main parameters that need to be controlled in both set point
and load changes.
A control system of propylene glycol production in a non isothermal (CSTR) was
developed in this work where the dynamic and control system based on basic mass
and energy balance were carried out.
Inlet concentration and temperature are the two disturbances, while the inlet
volumetric flow rate and the coolant temperature are the two manipulations. The
objective is to maintain constant temperature and concentration within the CSTR.
A dynamic model for non isothermal CSTR is described by a first order plus dead
time (FO
University of Baghdad college of Medicine - Cited by 1 - Human Anatomy
In this paper, introduce a proposed multi-level pseudo-random sequence generator (MLPN). Characterized by its flexibility in changing generated pseudo noise (PN) sequence according to a key between transmitter and receiver. Also, introduce derive of the mathematical model for the MLPN generator. This method is called multi-level because it uses more than PN sequence arranged as levels to generation the pseudo-random sequence. This work introduces a graphical method describe the data processing through MLPN generation. This MLPN sequence can be changed according to changing the key between transmitter and receiver. The MLPN provides different pseudo-random sequence lengths. This work provides the ability to implement MLPN practically
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