Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

It is a well-known fact that publishing companies spend much money, time and energy in designing their book covers to attract potential customers. As the first thing people do when they buy or intend to buy a book is looking at its front cover. However, if there is a need to know more about the book, people usually look at the information on its back cover. This paper attempts to explore the persuasive function of blurbs beyond the constraints of the academic domain and consequently their connection with advertising discourse in two main sections: The first presents the concept of blurb and its structure while the second defines persuasion and shows the most prominent strategiesused in blurbs. Finally, this paper gives the conclusion tha

    The research addressed the ecological impact of the industrial product as one of the basic aesthetic elements in urban design. The research discussed the nature of the overall ecosystems of the industrial product in urban spaces, and the type of impact they have on each other. The discussion of impacts started from the identification of cognitive and non-cognitive viewpoints in the vision of ecological aesthetics, passing through the inputs of cognitive systems that see that the ecosystem made of the urban space with the existence of the industrial product as one of its constituents, are in fact systems  based on functional symmetry   between urban space design and the  design of the industrial prod

            Felodipine is a calcium-channel blocker with low aqueous solubility and bioavailability. Lipid dosage forms are attractive delivery systems for such hydrophobic drug molecules. Nanoemulsion (NE) is one of the popular methods that has been used to solve the dispersibility problems of many drugs. Felodipine was formulated as a NE utilizing oleic acid as an oil phase, tween 80 and tween 60 as surfactants and ethanol as a co-surfactant. Eight formulas were prepared, and different tests were performed to ensure the stability of the NEs, such as particle size, polydispersity index, zeta potential, dilution test, drug content, viscosity and in-vitro drug release. Result

Azithromycin is the drug of choice in the treatment of several bacterial infections, most often those causing middle ear infection, bronchitis, pneumonia, typhoid and sinusitis. It’s also effective against certain urinary tract infections and venereal diseases. This study was carried out to prepare an acceptable suspension either as dry physical mixture powder or granules to be reconstituted, through studying the effect of various type and concentration of suspending agent (xanthan gum, hydroxypropyl methylcellulose (HPMC), either alone or in combination) on the release profile of the drug. The best prepared suspension formulas (H& III) were selected depending on the dissolution profile of each formulas and then compared with

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter