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Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned from Twitter content without modifying the basic topic model of LSA and LDA. Users who share the same hashtag at most discuss the same topic. We compare the performance of the two methods (LSA and LDA) using the topic coherence (with and without hashtags). The experiment result on the Twitter dataset showed that LSA has better coherence score with hashtags than that do not incorporate hashtags. In contrast, our experiments show that the LDA has a better coherence score without incorporating hashtags. Finally, LDA has a better coherence score than LSA and the best coherence result obtained from the LDA method was (0.6047) and the LSA method was (0.4744) but the number of topics in LDA was higher than LSA. Thus, LDA may cause the same tweets to discuss the same subject set into different clustering.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Sun Dec 01 2019
Journal Name
Ieee Xplore
A Hybrid Modified Lightweight Algorithm Combined of Two Cryptography Algorithms PRESENT and Salsa20 Using Chaotic System
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Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Study the Effect of 12-Hydroxyoctadecanoic Acid Concentration on Preparation and Characterization of Floating Organogels using Cinnarizin as Modeling Drug
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This work targeted studying organogel as a potential floating system. Organgel has an excellent viscoelastic properties, floating system posses a depot property.  Different formulations of 12-hydroxyoctadecanoic acid (HOA) in sesame oil were gelled and selecting F1, F3 and F5 HOA organogels for various examinations: tabletop rheology, optical microscopy, and oscillatory rheology studies. Also, the floating properties studies were conducted at in vitro and in-vivo levels. Lastly, the in-vitro release study using cinnarizine (CN) was to investigate the organogel depot property. Based on the results, the selected concentrations of HOA in sesame oil organogels showed temperature transitions fr

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Publication Date
Sat Mar 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The use of technology review and evaluate programs PERT to improve the cost method on the basis of activity: بحث تطبيقي في الشركة العامة للصناعات النسيجية /واسط
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Suffer most of the industrial sector companies from high Kperfi magnitude of the costs of industrial indirect, lack of equitable distribution of these costs on the objectives of cost, increased competition, and the lack of proper planning in line and changes faced by the industrial sector (general) and sample (private), as well as the difficulty in re- directing efforts to improve profitability and in-depth analysis of activities, and to identify untapped resource activities, then link these activities to the final products  The research aims to apply the technology review and evaluate programs with the method (ABC) through the application stages of planning, scheduling and control and a comparison to get to the products of dev

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Publication Date
Tue Jun 10 2025
Journal Name
Al–bahith Al–a'alami
EMPLOYING TWITTER IN THE U.S. PRESIDENTIAL ELECTION CAMPAIGN IN 2016: U.S. PRESIDENTIAL CANDIDATE DONALD TRUMP’S TWEETS AS A “MODEL”: (A Research Drawn from a Master’s Thesis) (An Analytical Study)
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This study aimed to identify the employment of the social networking platform «Twitter» in the 2016 presidential campaign led by the Republican candidate, Donald Trump; and analyse his tweets through his personal account on «Twitter»  for the period from: 10/ 8/2016 to: 11/ 8/2016 which represents the last month of the election campaign.

The study belongs to the type of descriptive studies using the analytical method through an analysis index that includes sub-categories and other secondary categories. The research has adopted the ordinary unit of information material (tweet) as an analysis unit for this purpose.

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Digital modeling and its technical variables in contemporary interior design
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The current research sheds light on an important aspect of the great and rapid development in the field of science and technology and modern manufacturing methods as a result of the scientific revolution resulting from the accelerated cognitive development, which prompted designers in general and interior design in particular to exploit and invest in digital technology and the development of digital control in the process of designing the industrial product for the purpose of creativity and innovation through these digital programs Digital models achieve the requirements and desires of the interior designer according to the creative skill using modern software with high efficiency And extreme accuracy that is consistent with the requirem

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Analytical Performance Modeling of InP-InGaAs Hetero-junction Avalanche Photodiode
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In this study, an analytical model depending on experimental results for InPInGaAs
avalanche photodiode at low bias was presented and the characteristics of
gain for this photodiode were determined directly by the impulse response. The
model have considered the most important mechanisms contributing the
photocurrent, they are trapping, photogeneration in the undepleted region and
charge-carriers velocity due to the built-in electrical field. Also, the bandwidth
was determined as a function to the total gain of photodiode and it was mainly
determined by diffusion and trapping processes at low gain regarding to the multilayer
structure considered in this study

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Wed Jun 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kinetic and Isotherm Modeling of Adsorption of Dyes onto Sawdust
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Sawdust has the ability to adsorb the dyestuff from aqueous solution. It may be useful low cost adsorbent for the treatment of effluents, discharged from textile industries. The effectiveness of sawdust has been tested for the removal of color from the wastewater samples containing two dyes namely Direct Blue (DB) and Vat Yellow (VY). Effect of various parameters such as agitation time, adsorbent dose and initial concentration of each dye has been investigated in the present study. The adsorption of dyes has been tested with various adsorption isotherm models. The Langmuir isotherms model is found to be the most suitable one for the dye adsorption using sawdust and the maximum adsorption capacity is 8.706 mg/g and 6.975 mg/g for DB and V

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Publication Date
Tue Oct 01 2019
Journal Name
2019 12th International Conference On Developments In Esystems Engineering (dese)
Structural Modeling of Cross-Frame Behavior in Steel Girder Bridges
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