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SAR-HDP: Non-parametric Topic Model for Aspect categorisation based on online reviews
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Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Process (HDP), named (SAR-HDP). The phrase-based (or aspect-based) Bayesian model (SAR-HDP) did not consider the words sentence being drawn from a single topic due to the presence of multiple aspects in a single review, which belonged to a multiple-aspect topic (i.e., category). Beyond its consideration of the semantic information for aspect identi cation, the proposed model further upheld the semantic information discerned between the drawn topics and aspects identi ed to maintain topic consistency. Empirical investigation showed that the approach positioned successfully outperformed standard parametric models and nonparametric models in terms of aspect categorisation when subjected to restaurant and hotel reviews sourced from Amazon and TripAdvisor.

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The impact of using learning acceleration model on the achievement of mathematics for third intermediate grade students
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The current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of The College Of Languages (jcl)
Negation marker in Standard Persian : a typological analysis based on Givon’s functional model: عامل نفی در زبان فارسی معیار: بررسی رده‌شناختی براساس مدل نقش‌ گرایی گیون
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 Abstract:

Typological analysis about  the negation marker  in different languages is one of the fields of research that has attracted much attention.  In Persian language, this constituent has been analysed from different aspects. This study aimed to analyse  different aspects of negation marker  in  the adjectives,  the noun phrases and  the verb phrases based on typological analysis.  Many studies have been revealed that  the negation in adjectives has shown lexically and morphologically. In the noun phrases, /hich/  has used as a negative marker necessarily marking the verb phrase as negative too. In the verb phrases, negation occurs morphologically by the addition of the prefix /n

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The role of financial reporting for non-current assets impairment in enhancing the relevance accounting information
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  This research deals with the financial reporting for the non-current assets impairment from the viewpoint of international accounting standards, especially IAS 36 "Impairment of assets”. The research problem focused on the non-compliance with the requirements of IAS 36 which would negatively affect the accounting information quality, and its characteristics, especially the relevance of accounting information, that confirms the necessity of having such information for the three sub-characteristics in order to be useful for the decisions of users represented

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Publication Date
Tue May 01 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
Evaluation of Electromagnetic Near-Field Measurement Technique as Non-Destructive Testing for Composite Structures
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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
The mucosal and systemic immune status for diabetic and non-diabetic Dentialvcolar infected patients
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From a group of 60 patients with dentoalveolar infections among which 10 were diabetic and 10 non-diabetic were elected as test group as well as 10 normal subjects as control group. Six Staphylococcus aureus and Streptococcus anginousus were diagnosed in the first and second group of the patients the immune status of the patients and control subject were tested by pathogen specific antibody titre, neotrophil NBT reduction phagocytosis and leukocyte inhibition LIF. Diabetic patients with dentoalveolar infection shows decreased specific antibody titers, subnormal neutrophil NBT phagocytic % as well as non significant LIF % in comparison non diabetic reveal high specific antibody titers against , high neutrophil NBT% and significant LIF% re

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
AGENT BASED MONITORING FOR INVESTIGATION PROCESS AND MAINTENANCE IMPROVEMENT
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Agent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
On the Laser Micro Cutting: Experimentation and Mathematical Modeling based on RSM-CCD
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The laser micro-cutting process is the most widely commonly applied machining process which can be applied to practically all metallic and non-metallic materials. While this had challenges in cutting quality criteria such as geometrical precision, surface quality and numerous others. This article investigates the laser micro-cutting of PEEK composite material using nano-fiber laser, due to their significant importunity and efficiency of laser in various manufacturing processes. Design of experiential tool based on Response Surface Methodology (RSM)-Central Composite Design (CCD) used to generate the statistical model. This method was employed to analysis the influence of parameters including laser speed,

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine 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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Publication Date
Tue Jan 01 2019
Journal Name
Cpwr
Development of a workforce sustainability model for construction
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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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