Objective: To assess the fear of laboring women regarding the delivery on themselves and their
newborns.
Methodology : A descriptive study was conducted on (100) pregnant women who where admitted to
labor room in Al- Yarmock Teaching Hospital/Maternity Units, Fatima Al- Zahra and Ibn-Al Baladi
Maternity and Pediatric Hospital. The questionnaire was consisted of pregnant women
socio-demographic data, reproductive data and fear items of labor. Data were collected by using a
questionnaire format, through interview technique and reviewing pregnant records, descriptive and
inferential statistical procedure were used to analyze the data.
Results: The main results of the study revealed a high mean of scores with moderate (RS) in women's
fear regarding labor on her self ( labor difficulties ,dying during labor, labor pain related to uterine
contractions, prolonged labor, fear of being left alone, fear of episiotomy, and exposure to infection )
And on their newborn in (delivery of unhealthy or abnormal newborn ,newborn death during or after
delivery, head dystocia, fetal asphyxia, and exposure to cold and infection ). The findings also
presented significant differences between women's fear regarding labor on themselves and socio
demographic and reproductive variables in (age, education, residency, socioeconomic status, history of
abortion, pregnancy &delivery complications ), and on their newborn in (age, education, type of family
.gravidity, parity, history of abortion, &pregnancy complications).
Recommendation: Educational program can be designed to orient the pregnant women toward
physiological and psychological changes during pregnancy, labor & delivery process and Initiation of
prenatal education classes in primary health care centers.
Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on
... Show MoreThis paper investigates some exact and local search methods to solve the traveling salesman problem. The Branch and Bound technique (BABT) is proposed, as an exact method, with two models. In addition, the classical Genetic Algorithm (GA) and Simulated Annealing (SA) are discussed and applied as local search methods. To improve the performance of GA we propose two kinds of improvements for GA; the first is called improved GA (IGA) and the second is Hybrid GA (HGA).
The IGA gives best results than GA and SA, while the HGA is the best local search method for all within a reasonable time for 5 ≤ n ≤ 2000, where n is the number of visited cities. An effective method of reducing the size of the TSP matrix was proposed with
... Show MoreThere is no doubt that the project control function is very important for administration, so the project Management depends on to monitor and control the project. The project control integrated to the planning which is the base of the administration functions; planning, organizing, directing, and controlling. Without project control cannot be insure to fulfill the plan of the project by the budget and specified time. The project management apply many methods of control to achieve the goals of project which are cost, time, and required specifications. Earned Value Management one of control methods that used in the project by international companies.
Earned Value Method is used in the project o
... Show MoreIn this work we study gamma modules which are implying full stability or implying by full stability. A gamma module is fully stable if for each gamma submodule of and each homomorphism of into . Many properties and characterizations of these classes of gamma modules are considered. We extend some results from the module to the gamma module theories.
Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.
The concept of the Extend Nearly Pseudo Quasi-2-Absorbing submodules was recently introduced by Omar A. Abdullah and Haibat K. Mohammadali in 2022, where he studies this concept and it is relationship to previous generalizationsm especially 2-Absorbing submodule and Quasi-2-Absorbing submodule, in addition to studying the most important Propositions, charactarizations and Examples. Now in this research, which is considered a continuation of the definition that was presented earlier, which is the Extend Nearly Pseudo Quasi-2-Absorbing submodules, we have completed the study of this concept in multiplication modules. And the relationship between the Extend Nearly Pseudo Quasi-2-Absorbing submodule and Extend Nearly Pseudo Quasi-2-Abs
... Show MoreCoronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing
... Show MoreThroughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.
This paper is concerned with introducing and studying the o-space by using out degree system (resp. i-space by using in degree system) which are the core concept in this paper. In addition, the m-lower approximations, the m-upper approximations and ospace and i-space. Furthermore, we introduce near supraopen (near supraclosed) d. g.'s. Finally, the supra-lower approximation, supraupper approximation, supra-accuracy are defined and some of its properties are investigated.
This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method
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