The huge amount of information in the internet makes rapid need of text
summarization. Text summarization is the process of selecting important sentences
from documents with keeping the main idea of the original documents. This paper
proposes a method depends on Technique for Order of Preference by Similarity to
Ideal Solution (TOPSIS). The first step in our model is based on extracting seven
features for each sentence in the documents set. Multiple Linear Regression (MLR)
is then used to assign a weight for the selected features. Then TOPSIS method
applied to rank the sentences. The sentences with high scores will be selected to be
included in the generated summary. The proposed model is evaluated using dataset
supplied by the Text Analysis Conference (TAC-2011) for English documents. The
performance of the proposed model is evaluated using Recall-Oriented Understudy
for Gisting Evaluation (ROUGE) metric. The obtained results support the
effectiveness of the proposed model.
Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had
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The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
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The research took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS
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ان الغرض من هذا البحث هو المزج بين القيود الضبابية والاحتمالية. كما يهدف الى مناقشة اكثر حالات مشكلات البرمجة الضبابية شيوعا وهي عندما تكون المشكلة الضبابية تتبع دالة الانتماء مرة دالة الاتنماء المثلثية مرة اخرى، من خلال التطبيق العملي والتجريبي. فضلا عن توظيف البرمجة الخطية الضبابية في معالجة مشكلات تخطيط وجدولة الإنتاج لشركة العراق لصناعة الأثاث، وكذلك تم استخدام الطرائق الكمية للتنبؤ بالطلب واعتماده
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Abstract
In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications in order to get mean square error and used it to make compare , simulation experiment contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif
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This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions, (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear
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The purpose of current study is to analyze the computer textbooks content for intermediate stage in Iraq according to the theory of multiple intelligence. By answering the following question “what is the percentage of availability of multiple intelligence in the content of the computer textbooks on intermediate stage (grade I, II) for the academic year (2017-2018)? The researcher followed the descriptive analytical research approach (content analysis), and adopted an explicit idea for registration. The research tool was prepared according the Gardner’s classification of multiple intelligence. It has proven validity and reliability. The study found the percentage of multiple intelligence in the content of computer textbooks for the in
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To determine the important pathogenic role of celiac disease in triggering several
autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years
have been investigated and compared with 25 healthy individuals. All the studied
groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG
by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial
antibodies IgA and IgG by IFAT. There was a significant elevation in the
concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to
control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin
antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies