In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin
... Show MoreDiabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreThis article discusses the function of semiotics in political discourse after the socio-political processes taking place in Iraq since 2003 and its role in the development of textual criticisms of some Iraqi politicians, analyzes the reasons for its functioning in the speech of politicians. The research is mainly focused on finding out to what extent political text studies draw on sign systems that can store and transmit information, the nature of its purpose and the use of available fields for the purpose to be achieved. The chief purpose of the study is to investigate and also clarify the symbols and signs appear within the framework of discursive Iraqi politicians, the nature of the symbols used, and the meanings that are include
... Show MoreThe research deals with the concept of stigma as one of the important phenomena that cast a shadow over the nature of the individual, his being and his personality through the inferior view with which he confronts in society, and (Sartors) indicates in this regard that stigma may lead to negative discrimination that leads to many defects, in terms of obtaining On care, poor health, service, and frequent setbacks that can damage self-esteem. The first roots of this phenomenon go back to the Greek civilization and what the Greeks used to burn and cut off some parts of the body and then announce to the nation that the bearer of this sign is a criminal. In addition to the Arab peoples living from setbacks that contributed to the exacerbation
... Show MoreTax state institution regards as one of the largest state institutions implementing the tax rules issuing be legislative body and achieving the goals of tax (financial, economic, social and political). So, the tax management should pay attention to the procedures enabling it to achieve those rules starting from the procedures of tax restrict and ending by tax allocation where the process of assessment the taxation must relaxing on modern methods. The problem of the study raising from that in spite of there is a low obliging the taxable person (registered or not) to submit a declaration about his income and the achieved profit to be the base of taxation˒ where the other ways are secondary ways helping in rejection of t
... Show MoreThis study examines strategies of cultural domestication in Muravyov and Kistyakovsky’s Russian translation of (The Fellowship of the Ring). It documents transformations of character names, toponyms, dialogues, and cultural references, highlighting systematic Russification and the infusion of Soviet political commentary that reshape the text into cultural rewriting.
Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak
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