Watermelon is known to be infested by multiple insect pests both simultaneously and in sequence. Interactions by pests have been shown to have positive or negative, additive or non additive, compensatory or over compensatory effects on yields. Hardly has this sort of relationship been defined for watermelon vis-à-vis insect herbivores. A 2-year, 2-season (4 trials) field experiments were laid in the Research Farm of Federal University Wukari, to investigate the interactive effects of key insect pests of watermelon on fruit yield of Watermelon in 2016 and 2017 using natural infestations. The relationship between the dominant insect pests and fruit yield were determined by correlation (r) and linear regression (simple and multiple) analys

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

The banks mobilize savings and channel them to the economy, whether commercial or Islamic banks and thus both contribute to increasing financial depth, the objective of this paper is to measure the contribution of the Islamic banks in increase financial depth in Iraq, and compared the role played by private commercial banks in contributing to increasing financial depth in Iraq. The paper has been applying the most used indicators of financial depth that used widely in the literatures, especially those applicable with the Iraqi economy.

The paper found via using the Autoregressive Distributed Lag Model (ARDL) that Islamic banks did not contribute to increasing financial depth in Iraq, as well as for the p

Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

Iraq has the second largest proven oil reserves in the world. According to oil experts, it is expected that the Iraq's reserves to rise to 200+ billion barrels of high-grade crude.

Oil is a strategic commodity for producing and exporting countries in general, and Iraq in particular, as demonstrated by the international experience that oil is an important means to achieve economic growth, an important tool in the overall economic, social and political development. It is also an important source of hard currency for any national economy and a means to connect the local economy and the global economy. In this paper we focus our attention on selecting the best regression model that explain the effect of human capita

Grey system theory is a multidisciplinary scientific approach, which deals with systems that have partially unknown information (small sample and uncertain information). Grey modeling as an important component of such theory gives successful results with limited amount of data. Grey Models are divided into two types; univariate and multivariate grey models. The univariate grey model with one order derivative equation GM (1,1) is the base stone of the theory, it is considered the time series prediction model but it doesn’t take the relative factors in account. The traditional multivariate grey models GM(1,M) takes those factor in account but it has a complex structure and some defects in " modeling mechanism", "parameter estimation "and "m

Radiation treatment has long been the conventional approach for treating nasopharyngeal cancer (NPC) tumors due to its anatomic features, biological characteristics, and radiosensitivity. The most common treatment for nasopharyngeal carcinoma is radiotherapy. This study aimed to assess the better quality of radiotherapy treatment techniques using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT). The VMAT and IMRT are comparative techniques. Forty patients with nasopharyngeal carcinoma and forwarded for radiotherapy were treated with both advanced techniques, IMRT and VMAT, using eclipse software from Varian. The x-ray energy was set at 6 MV. The total prescribed dose was 70 Gy. The results show that the