Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IHS), Principal Component Analysis (PCA), pyramid-based techniques, and transforming. Different quality metrics for quantitative analysis of these approaches have been debated.
Background: Joubert syndrome (JS) is a very rare autosomal recessive disorder characterized by agenesis of cerebellar vermis, abnormal eye movements, respiratory irregularities, and delayed generalized motor development. Retinal dystrophy and cystic kidneys may also be associated with this clinical syndrome. The importance of recognizing JS is related to the outcome and its potential complications. This syndrome is difficult to diagnose clinically because of its variable phenotype. Its neuroimaging hallmarks include the characteristic molar tooth sign and bat wing-shaped fourth ventricle
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreA- The research problem: the research problem which is the garments industry, as a
whole it does not rely on a single system in the sizes of the clothing and the working
companies, see that it is not plausible that the sizes be unificd and consistent in all companies.
The current sizes in the domestic Iraqi markets are not suitable for some females ,on the other
hand the Iraqi industry suffers the lack of a modern standard for some Iraqis female bodies.
B- The Signifiance of the research: lies in the study of the diversity of the human body
sizes and naming them to reflect the desires and requirements of the consumer and try to find
a method to meet their expectations as well as to raise the level of garments industr
A quadruped (four-legged) robot locomotion has the potential ability for using in different applications such as walking over soft and rough terrains and to grantee the mobility and flexibility. In general, quadruped robots have three main periodic gaits: creeping gait, running gait and galloping gait. The main problem of the quadruped robot during walking is the needing to be statically stable for slow gaits such as creeping gait. The statically stable walking as a condition depends on the stability margins that calculated particularly for this gait. In this paper, the creeping gait sequence analysis of each leg step during the swing and fixed phases has been carried out. The calculation of the minimum stability margins depends up
... Show MoreMaximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
... Show MoreIn this paper, there are two main objectives. The first objective is to study the relationship between the density property and some modules in detail, for instance; semisimple and divisible modules. The Addition complement has a good relationship with the density property of the modules as this importance is highlighted by any submodule N of M has an addition complement with Rad(M)=0. The second objective is to clarify the relationship between the density property and the essential submodules with some examples. As an example of this relationship, we studied the torsion-free module and its relationship with the essential submodules in module M.
The purpose of this paper is to statistically classify and categorize Building Information Modelling (BIM)-Facility Management (FM) publications in order to extract useful information related to the adoption and use of BIM in FM.
This study employs a quantitative approach using science mapping techniques to examine BIM-FM publications using Web of Science (WOS) database for the period between 2000 and April 2018.
The findi