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Learning English through Scaffolded Assistance in Iraqi EFL Classroom
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Learning a foreign language is a highly interactive process, and a belief that communicative activities foster a great amount of linguistic production provides language practice and opportunities for negotiation of meaning during communicative exchanges. Thus, this study examines what benefits learner-centered classroom setting offers compared with that of teacher–centered classroom, and how less proficient learners accomplish their tasks and activities with scaffolded help during interaction with the help of proficient classmates and under the guidance of a skilful person, i.e., the teacher. The subjects participating in this study are 30 Iraqi 4th year college students in the Department of English, College of Arts , University of Baghdad for the academic year 2012-2013. The students were working with groups of two or three. Their task was to make up different conversations and after each conversation, the teacher asked some questions to the group.

                Five teacher-student interactions were analysed. The results showed that learner-centeredness was beneficial for language learning in the following respects: 1-it triggered more scaffolding offered by the teacher and 2-interaction between learners actively occurred in learner – centered lessons. In addition when the teacher engaged in interaction with the students, he basically used repetition, paraphrases and nonverbal devices such as varying the pace of his/her utterances, facial expressions and pauses as scaffolding.

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Publication Date
Mon Sep 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
حول توزيع الطلب خلال فترة الانتظار عند خضوع الطلب لتوزيع گاما وفترة الانتظار للتوزيع اللوغاريتمي الطبيعي (I)
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سنقوم في هذا البحث باشتقاق توزيع الطلب خلال فترة الانتظار لنظام سيطرة على الخزين يخضع فيه الطلب لتوزيع گاما فيما يخضع وقت الانتظار للتوزيع اللوغايتمي الطبيعي، كما سيتم استخراج العزوم الأساسية لهذا المتغير ، الضرورية بدورها لاستخراج بعض مؤشرات النظام المذكور.

 

المصطلحات المستخدمة: التكامل المحيط، المستوي المركب، تكامل هانكيل، مستوى إعادة الطلب، الوقاية.

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Publication Date
Tue Feb 28 2023
Journal Name
Egyptian Journal Of Chemistry
Application of UV-A light Operating Photoreactor for Green Degradation of Direct Blue 15 through the Photo-Fenton-like process: Effects and Box-Behnken Optimization
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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Semiotics of Musical Sign in Iraqi Pantomime Show (Ahriman) as a Model: علي عدي صاحب-شيماء حسين طاهر
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The musical sign was associated with the first appearances of acting that are based on human gestures and expressive and silent movements, and they contributed in accentuating and clarifying these gestures and explain their meanings and indications, and they remained with them until these gestures turned into artistic theatrical shows so that the musical sign would have many functions and constitute the main pillars for this kind of show.
The musical sign is a language not much different than the human language in the semiotic analysis. There has been an increased interest in it and its use in the mime shows by the graduates who realized its necessity and significance in the pantomime show intellectually, artistically and aesthetical

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Publication Date
Tue Oct 30 2018
Journal Name
Risalat Al-huquq Journal
Legal Protection for Producers of Sound Recordings under Iraqi Law
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Piracy on phonograms is now, rightly, the crime of the electronic age. Despite the protection sought by States to provide for such registrations, whether at the level of national legislation or international agreements and conventions, but piracy has been and continues to pose a significant threat to the rights of the producers of those recordings, especially as it is a profitable way for hackers to get a lot of money in a way Illegal, which is contrary to the rules of legitimate competition. Hence, this research highlights the legal protection of producers of phonograms in light of the Iraqi Copyright Protection Act No. (3) of 1971, as amended.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Feb 15 2026
Journal Name
Journal Of Studies And Researches Of Sport Education
The effect of using the educational bag on the level of learning some offensive skills with the epee weapon
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Fri Jan 21 2022
Journal Name
Environmental Science And Pollution Research
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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