The present work describes numerical and experimental investigation of the heat transfer characteristics in a plate-fin, having built-in piezoelectric actuator mounted on the base plate (substrate). The geometrical configuration considered in the present work is representative of a single element of the plate-fin and triple fins. Air is taken as the working fluid. A performance data for a single rectangular fin and triple fins are provided for different frequency levels (5, 30 and
50HZ) , different input power (5,10,20,30,40 and 50W) and different inlet velocity (0.5, 1, 2, 3, 4, 5 and 6m/s) for the single rectangular fin and triple fins with and without oscillation. The investigation was also performed with different geometrical fin

The aim of the present research is to identify the test wisdom and the engagement with learning and psychological tension among postgraduate students at the University of Samarra according to the variables of the department, gender, age, and whether students are employee or non-employee. The study also attempts to identify the relationship between the test wisdom and the engagement with learning and psychological tension. The research sample consisted of (75) postgraduate students randomly selected from college of Education. The researcher applied the test–wisdom of (Mellman & Ebel) and the scale of engagement with learning preparation by (Al-zaabi 2013). In addition, the researcher used the list of the psychological stress of (Abu

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

This paper aims to add to the growing body of cognitive translation studies that deal with the translation of emotions and the factors of evaluating the translation process-oriented. Cognitive appraisal is one of the tokens that includes three paradigms of assessing the performance of translation, it can be addressed from the perspective of emotions, intuitions, and individual styles of the SL and the method of transfer into TL. The study hypothesized that translators create a similar emotional charge due to their mental capability to build the same emotional effect in the TL audience. The study also proposed that the applicability of cognitive appraisal is a valuable method of evaluating the translation process, as pertinent to TPR. The

Background: ?-L-Fucose is a methyl pentose sugar similar to L-galactose except for the loss of alcohol group on carbon number 6. The objective of this study is to evaluate the biochemical and antioxidant effect of intracrevicular injection of fucose into rabbits periodontium, throughout measuring the levels of total protein (TP), total fucose (TF), protein bound fucose PBF) , Malondialdehyde (MDA) , and vitamin C in sera of fucose injected rabbit groups. ) Materials and Methods: The existing study was carried out on 55 male rabbits and were divided randomly into three groups ; first group was injected with 50µl of 150mM fucose solution into gingival sulcus ; second group was injected with 50 µl of normal saline ; while the third group was