Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based data provided by Twitter API, Twitter places and Geocode parameters. We studied these methods to determine their accuracy and their suitability for research. The study concludes that the places method is the more accurate, but it excludes a lot of the data, while the geocode method provides us with more data, but special attention needs to be paid to outliers. Copyright © Research Institute for Intelligent Computer Systems, 2018. All rights reserved.
Heritage reflects peoples' memory and essence of nations. Thus, this divan was really the material and tool for writers in general and poets in specific both in their artificial innovations . Accordingly, modern writers have endeavored to bring heritage back in all its details and occurrences. Abdullwahab Al-Bayati's experience had reflected his innovative and strong link with the humanitarian heritage, in that heritage in view of Al-Bayati means both the humanitarian expertise and gains that are able to extend from past to future passing through the present.From this, the poet had not disconnected his strong link with the Arab poetic heritage .Thus, the poet had utilized the Arab poetic heritage in expressing on the Arab contrary realit
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Experimental investigation of the influence of inserting the metal foam to the solar chimney to induce natural ventilation are described and analyzed in this work. To carry out the experimental test, two identical solar chimneys (without insertion of metal foam and with insertion of metal foam) are designed and placed facing south with dimensions of length× width× air gap (2 m× 1 m× 0.2 m). Four incline angles are tested (20o,30o,45o,60o) for each chimney in Baghdad climate condition (33.3o latitude, 44.4o longitude) on October, November, December 2018. The solar chimney performance is investigated by experimentally recording absorber pl
... Show MoreIn this paper reliable computational methods (RCMs) based on the monomial stan-dard polynomials have been executed to solve the problem of Jeffery-Hamel flow (JHF). In addition, convenient base functions, namely Bernoulli, Euler and Laguerre polynomials, have been used to enhance the reliability of the computational methods. Using such functions turns the problem into a set of solvable nonlinear algebraic system that MathematicaⓇ12 can solve. The JHF problem has been solved with the help of Improved Reliable Computational Methods (I-RCMs), and a review of the methods has been given. Also, published facts are used to make comparisons. As further evidence of the accuracy and dependability of the proposed methods, the maximum error remainder
... Show MoreThe aim of the current research is to reveal the effect of using brain-based learning theory strategies on the achievement of Art Education students in the subject of Teaching Methods. The experimental design with two equal experimental and control groups was used. The experimental design with two independent and equal groups was used, and the total of the research sample was (60) male and female students, (30) male and female students represented the experimental group, and (30) male and female students represented the control group. The researcher prepared the research tool represented by the cognitive achievement test consisting of (20) questions, and it was characterized by honesty and reliability, and the experiment lasted (6) weeks
... Show MoreThe study aims mainly to evaluate the performance of Sharq Dijila water treatment plant in removing turbidity for the period of 1-4-2001 to 31-3-2004. Daily data for turbidity of raw, clarified, filtered, and supplied water were analyzed. The results of the study showed that there is a wide variation in turbidity levels of raw water fluctuating between 10-1000 NTU with mean value of 41.3 NTU. Turbidity values of the clarified water varied between 1.4-77 NTU. Based on the turbidity value of 10 NTU and 20 NTU (the design maximum turbidity) the readings gave an acceptable percentage of 32.4% and 86% respectively. The turbidity of filtered water ranged between 0.2-4.5 NTU which are completely in compliance with Iraqi and WHO standards. In ac
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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