Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

The analysis of detective novels has taken different aspects. The linguistic analysis of them, for example, has tackled the linguistic systems of morphology, phonology, syntax, semantics, and pragmatics. In line with the linguistic analysis, this study explores the various pragmatic and stylistic devices realized through detective novels for the purpose of misdirecting and deceiving the reader. The problem is that when readers try to reach to the truth, they face difficulties. They might not reach to the right solution or infer wrong conclusions because writers use some techniques to hide the truth and mislead them. This study aims at examining these techniques and devices; namely, Grice's Maxims and ambiguity as pragmatic devices on the

The study aimed to measure emotional purity, as well as to explore differences in it according to the variables of gender (male–female), academic level (first–fourth year), and field of specialization (scientific–humanities). The study adopted the descriptive-analytical method. The study instrument, a validated Emotional Purity Scale, was applied to a stratified random sample of 300 male and female students from the University of Baghdad. The results indicated that university students generally possess emotional purity. They also revealed significant differences in emotional purity attributed to gender in favor of females, to academic specialization in favor of humanities students, and to academic level in favor of fourth-year

The inner wasteland can be observed in Samuel Beckett’s early and later plays. His characters suffer from loss of identity, emotions, and sense of time. They lead a life of failure, repetition, inaction, loneliness, doubt, suffering, and nothingness. The inner wasteland includes many aspects, such as the multi and split identity, the habitual repetitive element of life, the dark sorrowful life the characters lead, lack of communication and relations among them, their unfree, inactive condition, their foggy terrible recollections, loneliness, dryness of love, and uncertainty. The analysis and the illustration of each aspect will show how the inner wasteland is intensified in the selected later plays of Beckett.

Background: Nanoparticles are clusters of atoms in a size range from (1-100) nm. Nano dentistry creates amazing useful structures from individual atoms or molecules (nanoparticles), which provides a new alternative and a possibly superior strategy in prevention and treatment of dental caries through management of dental plaque biofilms. The aim of the study was to test the sensitivity of Streptococcus mutans to different concentrations of hydroxyapatite and iron oxide nanoparticles suspension solutions, in comparison to chlorhexidine, and de-ionized water, in vitro. Materials and methods: Agar well technique was applied to test the sensitivity of Streptococcus mutans to different concentrations of hydroxyapatite and iron oxide nanoparticle

A novel ligand, (E)-5-((2-hydroxy-4,6-dimethylphenyl)diazenyl)-2,3-dihydrophthalazine-1,4- dione, was synthesized through the reaction of 3,5-dimethylphenol with the diazonium salt of 5-amino-2,3-dihydrophthalazine-1,4-dione. The ligand underwent characterization through the utilization of diverse spectroscopic methods, including UV-Vis, FT-IR, 13C, and 1H-NMR, alongside Mass spectroscopy and micro elemental analysis (Carbon, Hydrogen, Nitrogen, and Oxygen). Metal chelates of transition metals were prepared and analyzed using elemental analysis, mass spectra, atomic absorption, UV-Vis, FT-IR spectral analysis, as well as conductivity and magnetic measurements. The investigation into the compounds’ nature was conducted by utilizing mole r

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

Recently, the development and application of the hydrological models based on Geographical Information System (GIS) has increased around the world. One of the most important applications of GIS is mapping the Curve Number (CN) of a catchment. In this research, three softwares, such as an ArcView GIS 9.3 with ArcInfo, Arc Hydro Tool and Geospatial Hydrologic Modeling Extension (Hec-GeoHMS) model for ArcView GIS 9.3, were used to calculate CN of (19210 ha) Salt Creek watershed (SC) which is located in Osage County, Oklahoma, USA. Multi layers were combined and examined using the Environmental Systems Research Institute (ESRI) ArcMap 2009. These layers are soil layer (Soil Survey Geographic SSURGO), 30 m x 30 m resolution of Digital Elevati

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals