Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject area is the optimal self-organized service placement. In this paper a heuristic-based algorithm for service placement in future networks was presented. This algorithm achieves the ideal placement of services replicas by monitoring the load within the server and its neighborhood, choosing the node that contributes with the highest received load, and finally replicating or migrating the service to it based on specific criteria, so that the distance of requests coming from clients becomes as small as possible because of placing services within nearby locations. It was proved that our proposed algorithm achieves an improved performance by meeting the services within a shorter time, a smaller bandwidth, and thus a lower communication cost. It was compared with the traditional client-server approach and the random placement algorithm. Experimental results showed that the heuristic algorithm outperforms other approaches and meets the optimal performance with different network sizes and varying load scenarios.
We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed (LSD) to estimate the parameters an
... Show MoreIn this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients
... Show MoreMeta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1,
Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
... Show MoreThis research was carried out at University of Baghdad - College of Agricultural Engineering Sciences during the fall season of 2020 and spring season of 2021 in order to evaluate the effect of organic fertilizer and the foliar application of boron on the growth and yield of industrial potatoes (Solanum tuberosum L.). Using factorial experiment (5*4) within Randomized Complete Block Design with three replicates, the organic fertilizer (palm fronds peat) was applied at four levels (0, 12, 24, and 36 ton ha-1) in addition to the treatment of the recommended of chemical fertilizer. The foliar application of Boron was applied at four concentrations which were 0, 100, 150 and 200 mg (H3Bo3). L-1. The results Revealed a significant incr
... Show MoreAbstract:
If we neglect the value of historical fashions as a source of inspiration for
contemporary fashion designers we will neglect a treasure of original designs.
In neglecting such a treasure how could we then know what is original. Today
the most famous fashion designers are often inspired, in the outwardly from
and internal lines of their fashions, by fashion designed during the ages of the
past.
Designers can find such fashions in books of history and museums. But
the historical ages are not equal in the fertility of the originality and novelty of
their fashions. Thus the contemporary designer may not find the old designs
inspiring so he invents them.
The researcher was keen in this paper to inclu
The research aims to reveal the impact of media policy in Iraqi media outlets on the level of objectivity in these outlets. A study from the communicators’ point of view where the researcher used a survey method on the communicators in media outlets to reveal the extent of media policies knowledge as well as the pressures exerted by this policy on communicators in media outlets. It also reveals the extent of their commitment to objectivity, neutrality in dealing with information and the way used to transfer it.
The research sample included (179) respondents from communicators in a range of Media outlets such as (Press, Radio, and Television), The researcher was careful with the diversity of the sample, and
It included the introduction to the research and its importance, as the knee joint is one of the important joints in the human body that are susceptible to injury, and among these injuries is the roughness of the knee that occurs as a result of weakness and imbalance in the work of the quadriceps muscle, so its treatment is through rehabilitation exercises to treat weakness and gain flexibility and strength.Hence the importance of the research by developing rehabilitation exercises with different resistances in the water medium and restoring flexibility and muscular strength for patients with knee roughness for ages from 30-40 years, and the experimental method was used to solve the research problem, and the research sample included (6) of
... Show MoreGenerally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the
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