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.
A theoretical study including the effects of the fusion characteristics parameters on the fundamental fusion rate for the BEC state in D-D fusion reaction is deal with varieties physical parameters such as the fuels density, fuel temperature and the astrophysics S-factor are processed to bring an approximately a comparable results to agree with the others previously studies.
Purpose: This study's objective is to assess this relationship in the context of the banking industry in Iraq. The human resources management practices (HRMPs) Theoretical framework: in this study included recruiting and selection, training and development, performance appraisal, compensation and reward to testing relationship HRMPs. Design/methodology/approach: in this study; We analysed by used a quantitative approach, and 246 employees were selected as a sample and given a questionnaire. The SPSS software was used to examine the data that were obtained from the questionnaire. Findings: The study's findings revealed a variety of hypotheses and conclusions, including the following: comp
... Show MoreQuality function deployment tool is trying to improve health services through this study that will be applied in health sector environment , and be based on applying quality function deployment tool (QFD) TO preferable evaluation of main patients requirements in order to determine the technical requirements that need most attention across improving and developing health services .
Main requirements are determined to patients lying in the hospital (under research) which is (educational Baghdad \ medicine city office) in Baghdad, and other technical requirements through pers
... Show MorePurpose: This study's objective is to assess this relationship in the context of the banking industry in Iraq. The human resources management practices (HRMPs) Theoretical framework: in this study included recruiting and selection, training and development, performance appraisal, compensation and reward to testing relationship HRMPs. Design/methodology/approach: in this study; We analysed by used a quantitative approach, and 246 employees were selected as a sample and given a questionnaire. The SPSS software was used to examine the data that were obtained from the questionnaire. Findings: The study's findings revealed a variety of hypotheses and conclusions, including the following: competitive advantage (CA) is positively impacted by
... Show MoreComputer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi
... Show MoreIn this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.
... Show MoreIn this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.
Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce
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