In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.
Background: Thyroid surgery is most common endocrine surgery in general surgical practice. Objectives: the aim of this work is to evaluate the feasibility, benefits and outcomes of open mini-incision thyroidectomy and compared the results with that of conventional thyroidectomy. The comparison between the two groups was in term of incision length, amount of blood loss, time of operation, postoperative pain, hospital stay and the cosmetic outcomes.Type of the study: this is a single-blinded randomized controlled studyMethods: This study compared the advantages and outcomes of 22 patients subjected to mini-incision thyroidectomy (Group A) with the equal numbers of patients subjected to conventional thyroidectomy (Group B).Results: the oper
... Show MoreLow salinity (LS) water flooding is a promising EOR method which has been examined by many experimental studies and field pilots for a variety of reservoirs and oils. This paper investigates applying LS flooding to a heavy oil. Increasing the LS water temperature improves heavy oil recovery by achieving higher sweep efficiency and improving oil mobility by lowering its viscosity. Steam flooding projects have reported many problems such as steam gravity override, but override can be lessened if the steam is is alternated with hot LS water. In this study, a series of reservoir sandstone cores were obtained from Bartlesville Sandstone (in Eastern Kansas) and aged with heavy crude oil (from the same reservoir) at 95°C for 45 days. Five reservo
... Show MoreThe drones have become the focus of researchers’ attention because they enter into many details of life. The Tri-copter was chosen because it combines the advantages of the quadcopter in stability and manoeuvrability quickly. In this paper, the nonlinear Tri-copter model is entirely derived and applied three controllers; Proportional-Integral-Derivative (PID), Fractional Order PID (FOPID), and Nonlinear PID (NLPID). The tuning process for the controllers’ parameters had been tuned by using the Grey Wolf Optimization (GWO) algorithm. Then the results obtained had been compared. Where the improvement rate for the Tri-copter model of the nonlinear controller (NLPID) if compared with
Background: Removing dental plaque is important to maintain a good oral hygiene and prevent periodontal disease; this could not be accomplished by the use of toothbrush alone, it needs the help of interdental aids or intra-oral irrigator devices. The aim of this study was to compare the effect of using Waterpik flosser as adjunct to tooth brushing than using the dental floss with the brushing. Materials and methods: A single blind, six weeks study included 45 subjects divided into three groups of 15 subjects at each group. Group B (brushing) was instructed to use the toothbrush only, group BF (brushing & flossing) was instructed to use dental floss and tooth brushing while group BW (brushing and Waterpik flosser) was instructed to use Water
... Show MoreThis work presents a design for a pressure swing adsorption process (PSA) to separate oxygen from air with approximately 95% purity, suitable for different numbers of columns and arrangements. The product refill PSA process was found to perform 33% better (weight of zeolite required or productivity) than the pressure equalization process. The design is based on the adsorption equilibrium of a binary mixture of O2 and N2 for two of the most commonly used adsorbents, 5A & 13X, and extension from a single column approach. Zeolite 13X was found to perform 6% better than zeolite 5A. The most effective variables were determined to be the adsorption step time and the operational pressure. Increasing the adsorption step
... Show MoreRutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur
... Show MoreThe use of data envelopment analysis method helps to improve the performance of organizations in order to exploit their resources efficiently in order to improve the service quality. represented study a problem in need of the Iraqi Middle East Investment Bank to assess the performance of bank branches, according to the service quality provided, Thus, the importance of the study is to contribute using a scientific and systematic method by applying the data envelopment analysis method in assessing the service quality provided by the bank branches, The study focused on achieving the goal of determining the efficiency of the services quality provided by the bank branches manner which reflect the extent of utilization of a
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for