In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collected from the UCI Machine Learning Repository. The findings were discussed and summarized at the end. All calculations for this research have been done using R software (version 4.2.2). © 2024 Author(s).
Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide
... Show MoreKE Sharquie, JR Al-Rawi, AA Noaimi, HM Al-Hassany, Journal of drugs in dermatology: JDD, 2012 - Cited by 47
Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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Praise be to God, and prayers and peace be upon our master Muhammad, the Messenger of God, and upon his family, companions, and those who are guided by his guidance.
Then:
Our Islamic jurisprudence and its basic principles are fixed, namely: the Noble Qur’an, then the Prophet’s Sunnah, then consensus, then analogy. However, it is characteristic of what makes it developed to meet the requirements of renewed life, including: sent interests, custom, approval, blocking pretexts, changing times. That is why it went through different stages, growth, brilliance, stagnation and endowment; Therefore, many scholars of Islamic jurisprudence divided its stages into four sections: the stage of inf
... Show MoreThe purpose of this paper is to develop a hybrid conceptual model for building information modelling (BIM) adoption in facilities management (FM) through the integration of the technology task fit (TTF) and the unified theory of acceptance and use of technology (UTAUT) theories. The study also aims to identify the influence factors of BIM adoption and usage in FM and identify gaps in the existing literature and to provide a holistic picture of recent research in technology acceptance and adoption in the construction industry and FM sector.
The research seeks to study the subject (Media separation: the Relationship of Arab Immigrants with the Media of the Countries of Diaspora/ Sweden as a model). Where this phenomenon, "problem" has not been subjected to an in-depth study to find out the causes of this media separation and its repercussions on the immigrant, whether in the problem of integration, or his opportunity to work, or adapt to live in the new society.
Separation is a kind of word that is rarely used in Arabic media studies, relevant, sometimes, to the meaning of “refraining from watching TV or listening to the radio or reading newspapers”. Sometimes, it means “not tuning to or using any form of media like radios or newspapers to be updated about what
... Show MoreThe current study was carried out at the Fields belongs of Horticulture Department, Collage of Agricultural Engineering Science, University of Baghdad, Al-Jadiriyah for the spring season 2016 -2017 to study the effect for inoculation mycorrhizae and folair application with bio stimulators and their interaction in the growth characters of (local okra ptera). A factorial experiment (2 in randomized complete block design (RCBD), the experiment included (12) treatment Distributed in three replicates. The three factors used in this experiment included . The inoculation with control (C) Mycorrhizae ( M ) , Biozyme (B ) ( B1 2cm3.L-1), ( B2 4cm1-.L-1) , Phosphalas (P) (P 2cm3.L-1), ( M + B1), ( M + B2), (P +
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