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 categorical outcomes, with the overarching goal of supervised learning being to enhance models capable of predicting class labels based on input features. This review endeavors to furnish a concise, yet insightful reference manual on machine learning, intertwined with the tapestry of statistical learning theory (SLT), elucidating their symbiotic relationship. It demystifies the foundational concepts of classification, shedding light on the overarching principles that govern it. This panoramic view aims to offer a holistic perspective on classification, serving as a valuable resource for researchers, practitioners, and enthusiasts entering the domains of machine learning, artificial intelligence and statistics, by introducing concepts, methods and differences that lead to enhancing their understanding of classification methods.
Many biochemical and physiological properties depend on the size of ions and the thermodynamic quantities of ion hydration. The diffusion coefficient (D) of lanthanide (III) ions (Ln+3) in solution assumed (1.558-1.618 ×10−9 m2 s−1) by Einstein–Smoluchowski relation. The association constant (KA) of Ln+3 ions was calculated (210.3-215.3 dm3 mole-1) using the Shedlovsky method, and the hydrodynamic radius calculated (1.515-1.569 ×10−10 m) by the Stokes-Einstein equation. The thermodynamic parameters (ΔGo, ΔSo) also calculated by used suitable relations, while ΔHo, values are obtained from the lit
... Show MoreSage (Salvia officinalis), belong to Labiatae family is indigenous to Iraq and other Mediterranean areas but now cultivated world- wide, principally for its use as culinary herb. In the present study preliminary screening for the important phytochemical natural product groups indicated the presence of flavonoid, saponin, hyrolysable and condensed tannin groups. The antibacterial activity of two concentrations 10 mg/ml and 100 mg/ml of chloroform and hydroalcoholic extracts from Salvia officinalis leaves was evaluated against four strains of gram negative bacteria (Escherichia coli, Pseudomonas arigenossa, Klebsiella pneumonia, and Proteus spp) and two str
... Show MoreThis article will address autoclave design considerations and
manufacturing working with high pressure low temperature
supercritical drying technique to produce silica aerogel. The design
elects carbon dioxide as a supercritical fluid (31.7 oC and 72.3 bar).
Both temperature and pressure have independently controlling
facility through present design. The autoclave was light weight (4.5
kg) and factory-made from stainless steel. It contains a high pressure
window for monitoring both transfer carbon dioxide gas to liquid
carbon dioxide and watching supercritical drying via aerogel
preparation process. In this work aerogel samples were prepared and
the true apparent densities, total pore volume and pore size
Construction and operation of (2 m) parabolic solar dish for hot water application were illustrated. The heater was designed to supply hot water up to 100 oC using the clean solar thermal energy. The system includes the design and construction of solar tracking unit in order to increase system performance. Experimental test results, which obtained from clear and sunny day, refer to highly energy-conversion efficiency and promising a well-performed water heating system.
Six species of aquatic snails were sorted from three sites, the irrigation canal of Baghdad University campus (S1), River Tigris at Al-Za'afaraniah district / Baghdad(S2) , and River Euphrates at Al-Haideriah district Al-Najaf province(S2). The species included Melanopsis nodosa ;Melanoides tuberculata ; Thaiodaxsas jordani ; Lymnaea auricularia ; Physa acuta and Bellamya bengalensis. The first specis recorded the highest total number and was found in high density in the R. Euphrates site (S3), while the last species was the most widely distributed species, and found in all study sites. The last three species were found in Tigris river (S2) , while the first and last species were collected from the irrigation canal (S1).The result reveal
... Show Morethe behavior of the first-order black and gray solitons propagtedin optical fiber in the presence of frequency chirp is studied analytically and numerically results show that phase profile of black solitons changes abruptly
This paper is devoted to introduce weak and strong forms of fibrewise fuzzy ω-topological spaces, namely the fibrewise fuzzy -ω-topological spaces, weakly fibrewise fuzzy -ω-topological spaces and strongly fibrewise fuzzy -ω- topological spaces. Also, Several characterizations and properties of this class are also given as well. Finally, we focused on studying the relationship between weakly fibrewise fuzzy -ω-topological spaces and strongly fibrewise fuzzy -ω-topological spaces.
This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th
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