This paper proposes a collaborative system called Recycle Rewarding System (RRS), and focuses on the aspect of using information communication technology (ICT) as a tool to promote greening. The idea behind RRS is to encourage recycling collectors by paying them for earning points. In doing so, both the industries and individuals reap the economical benefits of such system. Finally, and more importantly, the system intends to achieve a green environment for the Earth. This paper discusses the design and implementation of the RRS, involves: the architectural design, selection of components, and implementation issues. Five modules are used to construct the system, namely: database, data entry, points collecting and recording, points reward

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil

We have focused the research problem through an assessment of the applicability of the third pillar of the decisions of the Basel Committee 11 (market discipline) or not and its impact on both the adequacy of bank capital, supervisory oversight and banking risks and the statement weaknesses commitment banking institutions and which in turn lead to the stability of the financial system as a whole.                         .
The research is important statement on the importance of big capital in the banking business and the attributes of a role in the absorption of losses suffered by the bank, which reflects the willin

The research aims to analysis of the current financial crisis in Iraq through knowing its causes and then propose some solutions that help in remedy the crisis and that on the level of expenditures and revenues, and has been relying on the Federal general budget law of the Republic of Iraq for the fiscal year 2016 to obtain the necessary data in respect of the current expenditures and revenues which necessary to achieve the objective of the research , and through the research results has been reached to a set of conclusions which the most important of them that causes of the current financial crisis in Iraq , mainly belonging to increased expenditures and especially the current ones and the lack of revenues , especially non-oil o

The study is about Maxwell , three dimensions of non – Newtonian fluid. Method of th Homotopy applied to analysis mass transfer and heat with thermophoresis effects. (Sc), Impact of therrmophoretic (𝜏), magnetic (M), Biot (γ), radiation (Rd),Schmidt Prandtle (Pr) parameters and ratio parameter(β) on concentration, temperature are offered in the paper.

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

The current study focuses on utilizing machine learning (ML) models in optimizing and predicting laser-induced surface cold hardening in aluminum alloy 6061-O using a pulsed fiber laser. Three input features were utilized: power density (Pd), frequency (f), and pulse overlap (OV), with surface hardness as the matching aim. A set of ML models, including XGBoost and Adaptive Ensemble, was employed. The dataset was preprocessed for normalization and outlier handling, hyperparameter tuning, and assessment through the grid search and cross-validation, and model performance was evaluated using the coefficient of determination (R²) and mean square error (MSE) metrics. The Linear regression and Random Forest regression models were excluded