As we know the transportation studies regarded as one of a very
important and difficult studies and one of its difficulties created from the
process of data updating therefore the researcher well facing many difficulties
to balancing between the old data on collecting new data.
The research present an opinion which is summarized by: can we use
the old data after we updated and used it as alternatives? Or the researcher
must collect new data to complete their research which indicate to the present
situation and some times they cant complete their studies because of the
security, economic, temporally difficulties.
The research used two kinds of data, the old data which belong to the
period (1998) and new data

Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2^nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

     Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

     Feature selection, a method of dimensionality reduction, is nothing but collecting a range of appropriate feature subsets from the total number of features. In this paper, a point by point explanation review about the feature selection in this segment preferred affairs and its appraisal techniques are discussed. I will initiate my conversation with a straightforward approach so that we consider taking care of features and preferred issues depending upon meta-heuristic strategy. These techniques help in obtaining the best highlight subsets. Thereafter, this paper discusses some system models that drive naturally from the environment are discussed and calculations are performed so that we can take care of the prefe

هدف البحث إلى معرفة تقويم الكفاءة الادارية لأعضاء اللجان المشرفة على التطبيقات التدريسية في كليات التربية بجامعة بغداد من وجهة نظر التدريسيين المشرفين عليها. اعتمد البحث المنهج الوصفي التحليلي. وتكون مجتمع البحث من (162) مشرفاً على التطبيقات التدريسية من كليات التربية/ جامعة بغداد، واختيرت عينة البحث بالطريقة العشوائية البسيطة، وبلغ عدد أفراد العينة (120) مشرفاً من الكليات آنفة الذكر. وتم بناء استبانة تضمنت (35)

حظيت عدد من الشخصيات التاريخية ممن كان لها أثر واضح المعالم في تطور النظام الإداري والسياسي للإمبراطورية المغولية، بأهتمام عدد لا بأس به من الباحثين.

      The current study is descriptive; it focuses on studying the contemporary geopolitical problem, and sectarian differences in Caucasus. Nagorno-Karabakh is considered an important disputed region nowadays. Many parties and states participated in this dispute, especially after the conflict had developed into an open war between Armenia and Azerbaijan. Thus, the study aims to examine the causes of the conflict in this region, analyze the international positions on this conflict, and find if Armenia was able to occupy this region. The methodology adopted by the researchers is the functional approach, and the theory of power analysis that Cohen created for analyzing all strengths that drove each of the parties t

The search in these subjects makes an importanl accomplishment in the study of the scientific life in that (era)   specialy what the wonen had from a scientific and social level in that(age) the studies of the scientestis which were brilliant in the this era never hed the same as the first scientests . because of the common mistakes toward some resesrchers