Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

The production companies in the Iraqi industry environment facing many of the problems related to the management of inventory and control In particular in determining the quantities inventory that should be hold it. Because these companies  adoption on personal experience and some simple mathematical methods which lead to the identification of inappropriate quantities of inventory.

       This research aims to identify the economic quantity of production and purchase for the Pepsi can 330ml and essential components in Baghdad soft drinks Company in an environment dominated by cases of non ensure and High fluctuating as a result of fluctuating demand volumes and costs ass

Each organization struggles to exploit each possible opportunity for gaining success and continuing with its work carrier. In this field, organization success can be concluded by fulfilling end user requirements combined with optimizing available resources usage within a specified time and acceptable quality level to gain maximum profit. The project ranking process is governed by the multi-criteria environment, which is more difficult for the governmental organization because other organizations' main target is maximizing profit constrained with available resources. The governmental organization should consider human, social, economic and many more factors. This paper focused on building a multi-criteria optimizing proje

water quality assessment is still being done at specific locations of major concern. The use of Geographical Information System (GIS) based water quality information system and spatial analysis with Inverse Distance Weighted interpolation enabled the mapping of water quality indicators along Tigris river in Salah Al-Din government, Iraq. Water quality indicators were monitored by taking 13 river samples from different locations along the river during Winter season year 2020. Maps of 10 water quality indicators. This meant that the specific water quality indicator and diffuse pollution characteristics in the basin were better illustrated with the variations displayed along the course of the river than conventional line graphs. Creation of

A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti

Objective: This study aimed to evaluate the effect of coating titanium (Ti) dental implant with polyether ketone ketone (PEKK) polymer using magnetron sputtering on osseointegration, trying to overcome some of the problems associated with Ti alloys. Material and Methods: Implants were prepared from grade (II) commercially pure titanium (CP Ti), then laser was used to induce roughness on the surface of Ti. PEKK was deposited on the surface of Ti implants by radiofrequency (RF) magnetron sputtering technique. The implants were divided in to three groups: without coating (Ls), with PEKK coating using argon (Ar) as sputtering gas (Ls-PEKK-Ar), and with PEKK coating using nitrogen (N) as sputtering gas (Ls-PEKK-N). All the implants were implante

The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel pr

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin