Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

Purpose: The diagnosis and determine the level of balance between the time available for life and work with the doctors in the hospitals of t the six hospitals in the City of Medicine.

Design / methodology / Approach: It has been relying on ready-scale, to make sure the diagnosis and determine the level of balance between the time available for life and work, where they were distributed on Form 42 doctors in the six hospitals in the City of Medicine, were analyzed by software (Nvivo and SPSS v.22).

Results: The results showed that there is a good level of balance between the time available for life and work with the doctors.

Research limitations: The diffi

     Task scheduling in an important element in a distributed system. It is vital how the jobs are correctly assigned for each computer’s processor to improve performance. The presented approaches attempt to reduce the expense of optimizing the use of the CPU. These techniques mostly lack planning and in need to be comprehensive. To address this fault, a hybrid optimization scheduling technique is proposed for the hybridization of both First-Come First-Served (FCFS), and Shortest Job First (SJF). In addition, we propose to apply Simulated Annealing (SA) algorithm as an optimization technique to find optimal job’s execution sequence considering both job’s entrance time and job’s execution time to balance them to reduce the job

Objective: This research aimed to study the relation between maximal bite force (MBF) and maximum mouth opening among 12-year-old school children. Methods: In this cross-sectional study, a total of 400 children aged 12 years (194 boys and 206 girls) were examined. The MBF for the right and left side, as well as the anterior region, were evaluated for all children. The MMO was measured using an electronic digital caliper. To analyze the data path analysis method was used. Results: Boys showed a higher MMO of 48.797 ± 6.500 than girls (46.710 ± 5.926 mm). The MMO increased with increasing MBF, with significant differences between females and males. Conclusion: The MMO was higher in boys than in girls. Gender plays a significant ro

The trading banks in Iraq invest their funds according to regulations imposed by the Central Bank in Iraq in different financial fields like stock exchanges, acquire stocks as assets that could be sold at any time as well as make loans and contributing in corporations establishment also magnitude foreign capital through direct contacts with foreign exchange markets.

We can summarize the problem of this paper as shortage in mathematical models that used in studying and analyzing these investments and according to this problem we used (a constructed mathematical model ) consists of three major indicators: profitability of total investment assets which is divided into three sub-indicators: owners equity risk indicator, debits risk i

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),