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bsj-6214
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acquisition and pre-processing, feature extraction, model development, visualization and viewing of word cloud model result. The results present an image in a series of text describing the top words. This model can be considered as a simple way to exchange high-level information without overloading the user's details.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Improve the Performance of PID Controller by Two Algorithms for Controlling the DC Servo Motor
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The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

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Publication Date
Tue Sep 28 2021
Journal Name
Journal Of The College Of Education For Women
The Degree of Knowledge and Use of Authentic Assessment Tools by Basic Elementary Teachers' According to some Variables: أمجد عزات جمعة، شريف عبد الرحمن السعودي، و سلمى علي العلوي
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Evaluation is one of the most important elements of  teaching process. The recent trends in evaluation and educational reform movements have called for using alternative evaluation, which focuses on performance evaluation. Authentic assessment is usually described as formative, in which students participate in their acquisition, in addition to the fact that students are productive and active, which is reflected in the students' achievement and skill level. The study aims to reveal the degree of knowledge and use of alternative assessment tools by primary school teachers in Gaza -Palestine. To meet the objective of the study, the researchers used the descriptive-analytical method and the questioner as a study tool. The study sample c

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Publication Date
Wed Jul 07 2021
Journal Name
جهاز التقيسس والسيطرة النوعية
تحضيروتشخيص ودراسة طيفية وحرارية وبيولوجية للمركب الجديد والمشتق من 2-امينوبينزوثايوزول واستخدامه كمثبط لتأكل سبيكة (-brass) في أنابيب مياه الشرب مع بعض المعقدات الفلزية
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تحضيروتشخيص ودراسة طيفية وحرارية وبيولوجية للمركب الجديد والمشتق من 2-امينوبينزوثايوزول واستخدامه كمثبط لتأكل سبيكة (-brass) في أنابيب مياه الشرب مع بعض المعقدات الفلزية

Publication Date
Tue Dec 31 2019
Journal Name
Arab Science Heritage Journal
جهود جُهُودُ عُلَمَاءِ العِرَاقِ في تَدْوِينِ الف هَ ا رِسِ والكَ ش ا فَاتِ والمَ جَ ل تِ المعْ ن يةِ بال ت راثِ
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The scholars of Iraq in the modern and contemporary era have been interested in the definition of tremendous knowledge treasures left by the successive Iraqi civilizations on Mesopotamia and around the cities, through the census and extrapolation of manuscript heritage and even printed, they compiled indexes,evidence

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Publication Date
Sun Jan 13 2019
Journal Name
Arab Science Heritage Journal
استخلاص عامل التلزن ( اللكتين ) من بكتريا لخلايا Enterococcus faecalis EM1 وتأثير العوامل البيئية المختلفة عليه ودوره في تلزن أنواع من البكتريا السالبة لملون غرام
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استخلص عامل التلزن من E. faecalis EM1 بعد تكسير الخلايا بعدة طرق واختيار الطريقة التي تعطي اعلى قيمة تلزن والترسيب بالكحول الاثيلي , واجري فحص التلزن وقياسه للمستخلص  مع انواع من البكتريا السالبة لملون غرام تضمنت     Escherichia coli  و Klebsiella  pneumoniae  و Serratia

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Tue Jan 12 2016
Journal Name
Wireless Networks
Low communication cost (LCC) scheme for localizing mobile wireless sensor networks
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In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Dynamic Response Assessment of the Nigerian 330kV Transmission System
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This paper presents the dynamic responses of generators in a multi-machine power system.  The fundamental swing equations for a multi-machine stability analysis are revisited. The swing equations are solved to investigate the influence of a three-phase fault on the network largest load bus. The Nigerian 330kV transmission network was used as a test case for the study. The time domain simulation approach was explored to determine if the system could withstand a 3-phase fault. The stability of the transmission network is estimated considering the dynamic behaviour of the system under various contingency conditions. This study identifies Egbin, Benin, Olorunsogo, Akangba, Sakete, Omotosho and Oshogbo as the key buses w

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Publication Date
Sun Apr 22 2018
Journal Name
Acs Biomaterials Science & Engineering
Engineered coatings for titanium implants to present ultra-low doses of BMP-7
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The ongoing research to improve the clinical outcome of titanium implants has resulted in the implementation of multiple approaches to deliver osteogenic growth factors accelerating and sustaining osseointegration. Here we show the presentation of human bone morphogenetic protein 7 (BMP-7) adsorbed to titanium discs coated with poly(ethyl acrylate) (PEA). We have previously shown that PEA promotes fibronectin organization into nanonetworks exposing integrin- and growth-factor-binding domains, allowing a synergistic interaction at the integrin/growth factor receptor level. Here, titanium discs were coated with PEA and fibronectin and then decorated with ng/mL doses of BMP-7. Human mesenchymal stem cells were used to investigate cellular resp

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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