This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreThe designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement
... Show MoreThe current research aimed to identify psychological stability and its relationship to university integration and spiritual intelligence among university students. The research sample consisted of (158) students from the College of Education - Al-Mustansiriya University.
A scale was applied: psychological stability, university integration, and spiritual intelligence, and by using the (Pearson) correlation coefficient, and the t-test, the results showed: the sample members enjoy psychological stability, university integration, and spiritual intelligence, and there is a positive, statistically significant correlation between the research variables, and the results resulted in some recommendations and proposals.
الخلفية: التهاب المفاصل الرَثَيَانِي أو الداء الرثياني أو الالتهاب المفصلي الروماتويدي هو مرض مزمن، من الأمراض الانضدادية التي تؤدي بالجهاز المناعي لمهاجمة المفاصل، مسببة التهابات وتدميرًا لها. ومن الممكن أيضًا أن يدمر جهاز المناعة أعضاء أخرى في الجسم مثل الرئتين والجلد. وفي بعض الحالات، يسبب المرض الإعاقة، مؤدية إلى فقدان القدرة على الحركة والإنتاجية. ويتم تشخيص المرض بواسطة تحاليل دم مخبرية مثل تحلي
... Show MoreSince the nineties of the last century, Iraqi youth have been exposed to Mexican soap operas dubbed into classical Arabic, and the stories and ideas presented by these series were almost new to all the minds of the youth at that time, a culture completely different from the culture we have of social relations, and since the number of episodes was more than Of the 100 episodes, exposure to these series has left young people confused by the addiction to all their ideas and stories. They differ from the foreign films (mostly American) that we used to watch, and they only take two hours (at most). These films contain diverse stories and may be forgotten. Memory includes events and characters in their entirety at times, and you may remember th
... Show MoreThe purpose of this study is to assess the level of computer literacy of the students at AlQuds open university in Tulkarm Branch. The study investigates the effects of the variables of gender, specialization, academic level, owning a personal computer, internet communication, and own an email account on the level of computer literacy. A test of computer literacy was constructed by the researchers consisting of (37) multiple choice items with a reliability rate (0.85). The study population consisted of (4100) students, while the sample contained (352) students. The study revealed that the level of computer literacy of the students at AlQuds Open University in Tulkarm Branch was (66.2 %) which is educationally acceptable. It also
... Show MoreThe present work aimed to study the effect of Grave's disease on the different tissues and organs of the body by using Wayne Thyrotoxicosis Diagnostic Index (WTDI) and Basel Metabolic Index (BMI). To reach such aim, (35) patients were involved (25 females and 10 males). A control group of (15) healthy individuals (10 females and 5 males) was selected for comparison , as well as , the following: 1- Wayne Thyrotoxicosis Diagnostic Index (WTDI) applied on patient group and control group under the supervision of specialist medical team , this index include (19) sign and symptom , the appearance of one of them may be lead to the others. The sings and symptoms of the index appear only on the patients. There is no Significant di
... Show MoreAchieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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