Municipal solid waste generation in Babylon Governorate is often affected by changes in lifestyles, population growth, social and cultural habits and improved economic conditions. This effect will make it difficult to plan and draw up future plans for solid waste management.In this study, municipal solid waste was divided into residential and commercial solid wastes. Residential solid wastes were represented by household wastes, while commercial solid wastes included commercial, institutional and municipal services wastes.For residential solid wastes, the relational stratified random sampling was implemented, that is the total population should be divided into clusters (socio-income level), a random sample was taken in e

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

The current study included measuring the percent of protein in the extract of nematode Ascaridia galli that infect chickens, it was 1.157% and equivalent to 11.570 mg /L., as well as the amino acid analysis in the nematode A.galli by using a high-performance liquid chromatography technique (HPLC), as was detect five types for amino acids in this extract Leucine, Threonin, Serine, Methionine and Valine as the amount of these amino acids in the extract was as follows 132.973, 26.994, 10.453, 2.243 and 1.888 mg /L., respectively, and other amino acids which Glutamic, Histidine and Tyrosin did not exist in the nematode A.galli.

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Broyden update is one of the one-rank updates which solves the unconstrained optimization problem but this update does not guarantee the positive definite and the symmetric property of Hessian matrix.

In this paper the guarantee of positive definite and symmetric property for the Hessian matrix will be established by updating the vector  which represents the difference between the next gradient and the current gradient of the objective function assumed to be twice continuous and differentiable .Numerical results are reported to compare the proposed method with the Broyden method under standard problems.

Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable) and glucose level in Bergman’s system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose

This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and