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.
This study was aimed to reduce the amount of the sprayed solution lost during trees spraying. At the same time, the concentration of the sprayed solution on the target (tree or bush) must be ensured and to find the best combination of treatments. Two factors controls the spraying process: (i) spraying speed (1.2 km/h, 2.4 km/h, 3.6 km/h), and (ii) the type of sensor. The test results showed a significant loss reduction percentage. It reached (6.05%, 5.39% and 2.05%) at the speed (1.2 km/h, 2.4 km/h, 3.6 km/h), respectively. It was noticed that when the speed becomes higher the loss becomes less accordingly. The interaction between the 3.6 km/h speed and the type of Ultrasonic sensor led to a decrease in the percentage of the spray
... Show MoreBackground: The objective of this study was to investigate the possibility of standardizing the Bolton ratio analysis as a diagnostic measure for both Iraqi and Egyptian orthodontic populations within three Angle' classification groups. Materials and methods: Two hundred forty pretreatment study casts (one hundred twenty of each population) were included in this study and divided into three Angle' classification groups. The mesiodistal crown diameters of all teeth were measured for computing the anterior and total Bolton ratios. Analysis of variance was performed to compare the mean ratios of Bolton analysis as a function of the Angle classification.HSD test was used to specify the classes of malocclusion that have significant differences.
... Show MoreComparisons of two life tables constructed to display alfaifa weevil Hypera posticoa (Gryllenhal), populations in southeentral Wisconsin, U. S. A. under epizootic and enzootic conditions of fungal diseasea, caused by Erynia phytonomi Arthur suggests that the “prepupal” stage provided the greates contribution to population changes under both conditions due to the high mortality rate. The principle mortality agents during this stage are E. phytonomi and the parasitoids complex of Bathyp1ectes curculionis and Buthyp1ectes anurus respectively under the two condition.
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
... Show MoreThermal decomposition of used tires was studied under atmospheric pressure and thermal heating program up to 350 °C for 110-120 min in a glass reactor. The effects of using MgO or SiO2 as catalyst in the thermal pyrolysis of tires waste on the yield ratio, reaction time, initial degree of decomposition also the contents of BTEX compounds in resulting pyrolytic oil was estimated via GC-FID. The results showed that the MgO catalyst gave a gas output in proportion of 17.063%, a liquid in a proportion of 38.245% and a solid product in proportion of 44.733%, while the SiO2 catalyst gave proportions of 14.308%, 40.161% and 45.448% for gas, liquid and solid products respectively. The results revealed that the thermal pyrolysis produced minor cont
... Show MoreBenign prostatic hyperplasia (BPH) is one of the most common disease and major cause of morbidity in elderly men which may lead to bladder outflow obstruction and lower urinary tract symptoms (LUTS). Although sex steroid hormones play fundamental roles in prostate growth, their clinical significance is not completely clear. In the present study we assessed whether serum hormones levels as markers of prostate disease. This study includes (40) patients with benign prostatic hypertrophy and (40) control group with age rang (41-79) and (42-71) years respectively. The following biochemical investigations have been studied: Testosterone, Estradiol (E2), and Prostatic Specific Antigen (PSA) levels using ELISA method which correlated with t
... Show MoreIn this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.
Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show More